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Last updated on September 25, 2017. This conference program is tentative and subject to change
Technical Program for Friday July 14, 2017
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FrAT1 Oral Session, Roentgen Hall |
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Signal Pattern Classification - Brain Computer Interface |
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Chair: Erdogmus, Deniz | Northeastern Univ |
Co-Chair: Guan, Cuntai | Nanyang Tech. Univ |
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08:00-08:15, Paper FrAT1.1 | Add to My Program |
Evaluation of Filtering Techniques to Extract Movement Intention Information from Low-Frequency EEG Activity |
Bibián, Carlos | Univ. Tübingen |
López-Larraz, Eduardo | Univ. of Tübingen |
Irastorza-Landa, Nerea | Univ. of Tübingen |
Birbaumer, Niels | Eberhard-Karls-Univ |
Ramos-Murguialday, Ander | Eberhard Karls Univ. of Tubingen/TECNALIA |
Keywords: Signal pattern classification
Abstract: Low-frequency electroencephalographic (EEG) activity provides relevant information for decoding movement commands in healthy subjects and paralyzed patients. Brain-machine interfaces (BMI) exploiting these signals have been developed to provide closed-loop feedback and induce neuroplasticity. Several offline and online studies have already demonstrated that discriminable information related to movement can be decoded from low-frequency EEG activity. However, there is still not a well-established procedure to guarantee that this activity is optimally filtered from the background noise. This work compares different configurations of non-causal (i.e., offline) and causal (i.e., online) filters to classify movement-related cortical potentials (MRCP) with six healthy subjects during reaching movements. Our results reveal important differences in MRCP decoding accuracy dependent on the selected frequency band for both offline and online approaches. In summary, this paper underlines the importance of optimally choosing filter parameters, since their variable response has an impact on the classification of low EEG frequencies for BMI.
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08:15-08:30, Paper FrAT1.2 | Add to My Program |
Reject Option to Improve Decoding Accuracy for EEG-Motor Imagery Based BCI |
M, Ganeshkumar | National Univ. of Singapore (NUS) |
So, Rosa | Inst. for Infocomm Res |
Ang, Kai Keng | Inst. for Infocomm Res |
Guan, Cuntai | Nanyang Tech. Univ |
Keywords: Signal pattern classification, Data mining and processing - Pattern recognition, Data mining and processing in biosignals
Abstract: The Filter Bank Common Spatial Pattern (FBCSP) algorithm had been shown to be effective in performing multi-class Electroencephalogram (EEG) decoding of motor imagery using the one-versus-the-rest approach on the BCI Competition IV Dataset IIa. In this paper, we propose a method to improve the accuracy of decoding further through a rejection option based on the difference in the posterior probability computed by the Naïve Bayesian classifier. We applied the proposed approach on the BCI Competition IV Dataset IIa, and the results showed an increase in the session-to-session transfer accuracy from 0.824% to 14.0%, but the average decoded trials decreased from 93.2% to 34.2% using a rejection threshold between 0.1 to 0.9. We subsequently formulated a method to optimize the rejection threshold based on the maximum F0.5 score. The optimal rejection threshold yielded an average increase in accuracy of 5.1% with an average of 67.5% of trials decoded. The results showed the feasibility of improving decoding accuracy at a cost of rejection. Nevertheless, the results suggest that the use of reject option may be used as a training feedback system to train subjects’ overt and covert EEG control strategies.
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08:30-08:45, Paper FrAT1.3 | Add to My Program |
Decoding Complex Imagery Hand Gestures |
Mohseni Salehi, Seyed Sadegh | Northeastern Univ |
Moghadamfalahi, Mohammad | Northeastern Univ |
Quivira, Fernando | Northeastern Univ |
Piers, Alexander | Northeastern Univ |
Nezamfar, Hooman | Northeastern Univ |
Erdogmus, Deniz | Northeastern Univ |
Keywords: Signal pattern classification, Physiological systems modeling - Signal processing in physiological systems, Data mining and processing - Pattern recognition
Abstract: Brain computer interfaces (BCIs) offer individuals suffering from major disabilities an alternative method to interact with their environment. Sensorimotor rhythm (SMRs) based BCIs can successfully perform control tasks; however, the traditional SMR paradigms intuitively disconnect the control and real task, making them non-ideal for complex control scenarios. In this study, we design a new, intuitively connected motor imagery (MI) paradigm using hierarchical common spatial patterns (HCSP) and context information to effectively predict intended hand grasps from electroencephalogram (EEG) data. Experiments with 5 participants yielded an aggregate classification accuracy--intended grasp prediction probability--of 64.5% for 8 different hand gestures, more than 5 times the chance level.
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08:45-09:00, Paper FrAT1.4 | Add to My Program |
Context-Aware Recursive Bayesian Graph Traversal in BCIs |
Mohseni Salehi, Seyed Sadegh | Northeastern Univ |
Moghadamfalahi, Mohammad | Northeastern Univ |
Nezamfar, Hooman | Northeastern Univ |
Haghighi, Marzieh | Northeastern Univ |
Erdogmus, Deniz | Northeastern Univ |
Keywords: Signal pattern classification, Data mining and processing - Pattern recognition, Physiological systems modeling - Signals and systems
Abstract: Noninvasive brain computer interfaces (BCI), and more specifically Electroencephalography (EEG) based systems for intent detection need to compensate for the low signal to noise ratio of EEG signals. In many applications, the temporal dependency information from consecutive decisions and contextual data can be used to provide a prior probability for the upcoming decision. In this study we proposed two probabilistic graphical models (PGMs), using context information and previously observed EEG evidences to estimate a probability distribution over the decision space in graph based decision-making mechanism. In this approach, user moves a pointer to the desired vertex in the graph in which each vertex represents an action. To select a vertex, a “Select” command, or a proposed probabilistic Selection criterion (PSC) can be used to automatically detect the user intended vertex. Performance of different PGMs and Selection criteria combinations are compared over a keyboard based on a graph layout. Based on the simulation results, probabilistic Selection criterion along with the probabilistic graphical model provides the highest performance boost for individuals with pour calibration performance and achieving the same performance for individuals with high calibration performance.
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09:00-09:15, Paper FrAT1.5 | Add to My Program |
Motor Imagery Classification of Upper Limb Movements Based on Spectral Domain Features of EEG Patterns |
Samuel, Oluwarotimi Williams | Shenzhen Inst. of Advanced Tech |
Li, Xiangxin | Shenzhen Inst. of Advanced Tech. Acad. of Sc |
Geng, Yanjuan | Shenzhen Inst. of Advanced Tech |
Fang, Peng | Shenzhen Inst. of Advanced Tech. Chinese Acad. of S |
Chen, Shixiong | Shenzhen Inst. of Advanced Tech |
Li, Guanglin | Shenzhen Inst. of Advanced Tech |
Keywords: Signal pattern classification, Data mining and processing - Pattern recognition
Abstract: Surface electromyography pattern recognition methods have been widely applied to decode limb movement intentions for prosthesis control. These methods generally require amputees to provide sufficient myoelectric signals from their residual limb muscles. Previous studies have shown that amputees with high level amputation or neuromuscular disorder usually do not have sufficient residual limb muscles to provide enough myoelectric signals for accurate identification of limb movements. Electroencephalography (EEG), another bioelectric signal associated with limb movements has also been proposed and used for decoding the limb motion intents of humans. With an attempt to improve the performance of EEG-based method in identifying multiple classes of upper limb movement intents, four spectral domain features of EEG were proposed in this study. Motor imagery patterns associated with five different classes of imagined upper limb movements were distinctively decoded based on the four features extracted from 64-channel EEG recordings in four transhumeral amputees. Experimental results show that an average accuracy of 97.81% was achieved across all the subjects and limb movement classes. By applying a sequential channel selection method, an accuracy of around 95.00% was realized with about 20-channels of EEG. Thus, the proposed method might be potential for providing accurate control input for neuroprosthesis.
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09:15-09:30, Paper FrAT1.6 | Add to My Program |
A Robust Beamforming Approach for Early Detection of Readiness Potential with Application to Brain-Computer Interface Systems |
mahmoodi, maryam | Tehran Univ. of Medical Sciences |
Makki Abadi, Bahador | Tehran Univ. of Medical Sceinces |
khajehpour, Hassan | Tehran Univ. of Medical Sciencies |
harirchian, mohammad hosein | Medical Sciences/univ. Tehran |
Keywords: Adaptive filtering
Abstract: Early detection of intention to move, at self-paced voluntary movements from the activities of neural current sources on the motor cortex, can be an effective approach to brain-computer interface (BCI) systems. Achieving high sensitivity and pre-movement negative latency are important issues for increasing the speed of BCI and other rehabilitation and neurofeedback systems used by disabled and stroke patients and helps enhance their movement abilities. Therefore, developing high-performance extractors or beamformers is a necessary task in this regard. In this paper, for the sake of improving the beamforming performance in well reconstruction of sources of readiness potential, related to hand movement, one kind of surface spatial filter (spherical spline derivative on electrode space) and the linearly constrained minimum variance (LCMV) beamformer are utilized jointly. Moreover, in order to achieve better results, the real head model of each subject was created, using individual head MRI, and was used in beamformer algorithm. Also, few optimizations were done on reconstructed source signal powers to help our template matching classifier with detection of movement onset for five healthy subjects. Our classification results show an average true positive rate (TPR) of 77.1% and 73.1%, false positive rate (FPR) of 28.96% and 28.74% and latency of -512.426±396.7ms and -360.29±252.16 ms from signals of current sources of motor cortex and sensor space respectively. It can be seen that the proposed method has reliable sensitivity and is faster in prediction of movement onset and more reliable to be used for online BCI in future.
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FrAT2 Oral Session, Cho Room |
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Ultrasound Imaging - Elastography I |
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Chair: Managuli, Ravi | Hitachi Aloka Medical America, Inc |
Co-Chair: Kwon, Hyock Ju | Univ. of Waterloo |
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08:00-08:15, Paper FrAT2.1 | Add to My Program |
ARFI Variance of Acceleration (VoA) for Noninvasive Characterization of Human Carotid Plaques in Vivo |
Torres, Gabriela | Univ. of North Carolina at Chapel Hill and North Carolina S |
Czernuszewicz, Tomasz | Univ. of North Carolina at Chapel Hill |
Homeister, Jonathon | Univ. of North Carolina at Chapel Hill |
Farber, Mark | Univ. of North Carolina at Chapel Hill |
Gallippi, Caterina | The Univ. of North Carolina at Chapel Hill |
Keywords: Ultrasound imaging - Elastography, Ultrasound imaging - Vascular imaging
Abstract: Rather than degree of stenosis, assessing plaque structure and composition is relevant to discerning risk for plaque rupture with downstream ischemic event. The structure and composition of carotid plaque has been assessed noninvasively using Acoustic Radiation Force Impulse (ARFI) ultrasound imaging. In particular, ARFI-derived peak displacement (PD) estimations have been demonstrated for discriminating soft (lipid rich necrotic core (LRNC) or intraplaque hemorrhage (IPH)) from stiff (collagen (COL) or calcium (CAL)) plaque features; however, PD did not differentiate LRNC from IPH or COL from CAL. The purpose of this study is to evaluate a new ARFI-based measurement, the variance of acceleration (VoA), for differentiating among soft and stiff plaque components. Both PD and VoA results were obtained in vivo for a human carotid plaque acquired in a previous study and matched to a histological standard analyzed by a pathologist. With VoA, plaque feature contrast was increased by an average of 60% in comparison to PD.
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08:15-08:30, Paper FrAT2.2 | Add to My Program |
The Influence of Hepatic Steatosis on the Evaluation of Fibrosis with Non-Alcoholic Fatty Liver Disease by Acoustic Radiation Force Impulse |
Guo, Yanrong | Shenzhen Univ |
Lin, Haoming | Shenzhen Univ |
Zhang, Xin-Yu | Shenzhen Univ |
Wen, Huiying | Shenzhen Univ |
Chen, Siping | Shenzhen Univ |
Chen, Xin | Shenzhen Univ |
Keywords: Ultrasound imaging - Elastography, Ultrasound imaging - Other organs
Abstract: Acoustic radiation force impulse (ARFI) elastography is a non-invasive method for the assessment of liver by measuring liver stiffness. The aim of this study is to evaluate the accuracy of ARFI for the diagnosis of liver fibrosis and to assess impact of steatosis on liver fibrosis stiffness measurement, in rats model of non-alcoholic fatty liver disease (NAFLD). The rat models were conducted in 59 rats. The right liver lobe was processed and embedded in a fabricated gelatin solution. Liver mechanics were measured using shear wave velocity (SWV) induced by acoustic radiation force. In rats with NAFLD, the diagnostic performance of ARFI elastography in predicting severe fibrosis (F ≥ 3) and cirrhosis (F ≥ 4) had the areas under the receiver operating characteristic curves (AUROC) of 0.993 and 0.985. Among rats mean SWV values were significantly higher in rats with severe steatosis by histology compared to those mild or without steatosis for F0-F2 fibrosis stages (3.07 versus 2.51 m/s, P = 0.01). ARFI elastography is a promising method for staging hepatic fibrosis with NAFLD in rat models. The presence of severe steatosis is a significant factor for assessing the lower stage of fibrosis.
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08:30-08:45, Paper FrAT2.3 | Add to My Program |
Application of Compressive Sensing to Portable Ultrasound Elastography |
Shin, Bonghun Shin | Univ. of Waterloo |
Jeon, Soo | Univ. of Waterloo |
Ryu, Jeongwon | Healcerion Inc |
Kwon, Hyock Ju | Univ. of Waterloo |
Keywords: Ultrasound imaging - Elastography, Image reconstruction and enhancement - Compressive sensing/sampling, Image retrieval
Abstract: Feasibility of applying compressive sensing (CS) to ultrasound radio-frequency (RF) data to produce elastography is investigated. The research also compares the performance of various CS frameworks associated with three common model bases (Fourier transform, discrete cosine transform (DCT), and wave atom (WA)) and two reconstruction algorithms (l_1 minimization and block sparse Bayesian learning (BSBL)) using the quality of B-mode images and elastograms from the RF data subsampled and reconstructed by each framework. Results suggest that CS reconstruction adopting BSBL algorithm with DCT model basis can yield the best results for all the measures tested, and the maximum data reduction rate for producing readily discernable elastograms is around 60%.
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08:45-09:00, Paper FrAT2.4 | Add to My Program |
Radiofrequency Ultrasound Data Acquisition with a 640-Element Array Transducer for Strain Imaging: Experimental Results with Phantoms and Biological Tissue Samples |
BRUSSEAU, Elisabeth | CREATIS |
BERNARD, Adeline | CREATIS |
MEYNIER, Cyril | VERMON |
FERIN, Guillaume | VERMON |
NGUYEN-DINH, An | VERMON |
BASSET, Olivier | CREATIS |
Keywords: Ultrasound imaging - Elastography
Abstract: This paper presents ultrasound elastography results obtained with a 640-element array transducer we have recently developed. This probe allows the acquisition of series of three adjacent imaging planes over time and therefore makes possible the computation of 2-D elastograms, with consideration of out-of-plane motion. In this study, elastography experiments were conducted on phantoms and bovine tissue samples, and compression was manually applied to the media via the hand-held ultrasound transducer. The results obtained with the proposed data acquisition and 3-D processing are presented and compared to those from a classical 2-D approach.
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09:00-09:15, Paper FrAT2.5 | Add to My Program |
Measurement of Surface Acoustic Waves in High-Frequency Ultrasound: Preliminary Results |
Saavedra, Ana Cecilia | Pontificia Univ. Católica Del Perú |
Zvietcovich, Fernando | Univ. of Rochester |
Lavarello, Roberto | Pontificia Univ. Catolica Del Peru |
Castañeda, Benjamín | Pontificia Univ. Católica Del Perú |
Keywords: Ultrasound imaging - Elastography, Ultrasound imaging - High-frequency technology
Abstract: Skin lesions change elastic properties near the surface. In the last decades, several non-invasive elastography techniques have been developed for detecting the mechanical properties of tissue. In particular, harmonic elastography is characterized for inducing shear wave propagation by an external vibrator in order to estimate shear modulus. However, near the boundary region, propagation is governed by surface acoustic waves (SAW). This paper combines crawling waves elastography with a high-frequency ultrasound (HFUS) system for the estimation of the SAW-to-shear compensation factor when ultrasound gel (US gel) is used as coupling interface. Experiments explore the SAW speed in a homogeneous phantom with a solid-water interface in order to corroborate theoretical findings. Subsequently, experiments in a solid-US gel interface are conducted in order to find the correct compensation factor. Preliminary results suggest that SAW propagation can be detected using HFUS, and shear velocity maps can be generated by applying the estimated empirical correction factor. This study will potentially avoid the underestimation of shear modulus when using SAW-based HFUS elastography which is promising for the better diagnosis of skin diseases.
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09:15-09:30, Paper FrAT2.6 | Add to My Program |
Shear Wave Estimation by Using Shear Wave Holography with Normal Vibration: Preliminary Results |
Arroyo, Junior | Pontificia Univ. Católica Del Perú |
Castañeda, Benjamín | Pontificia Univ. Católica Del Perú |
Keywords: Ultrasound imaging - Elastography
Abstract: Mechanical properties of soft human tissue are linked to their pathological state. One way to assess these properties is through the Young modulus measurement, which is related to the shear wave speed in the medium. In order to characterize its elastic properties using sonoelastography, we introduce a new technique for shear wave estimation from a static interference pattern based on Shear Wave Holography. A relation between the mathematical representation of the interference pattern and the local shear speed is derived using the Phase Derivative approach. The experimental scheme is presented, detailing the advantages of the new configuration. Homogeneous and heterogeneous elastic media were simulated, generating an interference pattern on them. The shear speed estimation algorithm was explained and applied to obtain the speed map, calculating the mean value over each medium. The technique was tested on a homogeneous elastic phantom, yielding an estimation error of 6%. Overall, Shear Wave Holography using normal vibration is feasible and shows promising results in estimating shear wave speed in elastic materials.
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FrAT3 Oral Session, Park Room |
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MRI Neuroimaging |
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Chair: Wang, Yi | Cornell Univ |
Co-Chair: Wang, Ze | Temple Univ |
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08:00-08:15, Paper FrAT3.1 | Add to My Program |
Central Sulcus Depth and Sulcal Profile Differences between Congenitally Blind and Sighted Individuals |
James, Clarissa | Univ. of Southern California |
Lepore, Franco | Univ. of Montreal |
Collignon, Olivier | Univ. Catholique De Louvain |
Lepore, Natasha | Univ. of Southern California / Children's Hospital Los Ange |
Coulon, Olivier | Aix-Marseille Univ |
Keywords: Magnetic resonance imaging - MR neuroimaging
Abstract: We used BrainVisa software in an exploratory analysis measuring the depth and sulcal profile of the central sulci of congenitally blind and sighted individuals. We found the greatest differences between the groups at locations on the central sulcus corresponding with the pli de passage fronto-parietal moyen (PPFM), suggesting a cortical reorganization of the primary sensorimotor area of the hand within the central sulcus. This may be in response to the congenitally blind individuals’ mastery of Braille or general increase of hand use in everyday life.
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08:15-08:30, Paper FrAT3.2 | Add to My Program |
MRI Based Objective Ischemic Core-Penumbra Quantification in Adult Clinical Stroke |
Vupputuri, Anusha | Indian Inst. of Tech. Kharagpur |
Ashwal, Stephen | Department of Pediatrics, Loma Linda Univ. Loma Linda, CA |
Tsao, Bryan | Department of Neurology, Loma Linda Univ. Loma Linda, CA 9 |
Haddad, Elia | Department of Neurology, Loma Linda Univ. Loma Linda, CA 9 |
Ghosh, Nirmalya | Indian Inst. of Tech. Kharagpur |
Keywords: Magnetic resonance imaging - MR neuroimaging, Image segmentation, Multimodal imaging
Abstract: Objective and non-invasive quantification of ischemic stroke and differentiation of salvageable from non-salvageable tissue is critical to treatment planning. However current Magnetic Resonance Imaging(MRI) techniques are time consuming and rely on manual detection methods. Computer aided preliminary screening of the injured tissue could assist neuroradiologists in performing more detailed analysis of the lesion components. An established Hierarchical Region Splitting (HRS) method was extended to segment lesions from adult patients who suffered a clinical stroke using diffusion- and perfusion weighted image (DWI-PWI) maps and associated computed maps. Apart from lesion quantification PWI-DWI based HRS was also able to automatically quantify core (irrecoverable) the penumbra (potentially recoverable) which helped to estimate salvageable tissue. The PWI-DWI/HRS results were validated by comparing with manually demarcated ground truth in terms of performance indices like lesion volume (82.1% accuracy), sensitivity (78.8%), specificity (99.3%) and similarity (78.54%) for a dataset of 10 acute adult stroke patients. Datasets were classified into severe, moderate and mild injuries based on total lesion volume. Proposed PWI-DWI/HRS method demonstrated accuracy close to manual lesion demarcation with high performance indices for core and penumbra in severe and moderate classes.
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08:30-08:45, Paper FrAT3.3 | Add to My Program |
Brain Functional Connectivity Alterations in a Rat Model of Excessive Alcohol Drinking: A Resting-State Network Analysis |
Pérez-Ramírez, Úrsula | Univ. Pol. De València |
Díaz-Parra, Antonio | Univ. Pol. De València |
Ciccocioppo, Roberto | School of Pharmacy Univ. of Camerino, Camerino, Italy |
Canals, Santiago | Inst. De Neurociencias, Consejo Superior De Investigaciones |
Moratal, David | Univ. Pol. De València |
Keywords: Magnetic resonance imaging - MR neuroimaging, Brain image analysis, Functional image analysis
Abstract: Alcohol use disorders (AUD) are a major public health concern. Understanding the brain network alterations is of the utmost importance to diagnose and develop treatment strategies. Employing resting-state functional magnetic resonance imaging, we have performed a longitudinal study in a rat model of chronic excessive alcohol consumption, to identify functional alterations in brain networks triggered by alcohol drinking. Two time points were considered: 1) before alcohol consumption (control condition) and 2) after 30 days of alcohol drinking (alcohol condition). We first identified nine resting-state networks with group independent component analysis. Afterwards, dual regression was applied to obtain subject-specific time courses and spatial maps. L2-regularized partial correlation analysis between pairs of networks showed that functional connectivity (FC) between the retrosplenialvisual and striatal networks decreases due to alcohol consumption, whereas FC between the prefrontal-cingulate and striatal networks increases. Analysis of subject-specific spatial maps revealed FC decreases within networks after alcohol drinking, including the striatal, motor-parietal, prefrontalcingulate, retrosplenial-visual and left motor-parietal networks. Overall, our results unveil a generalized decrease in brain FC induced by alcohol drinking in genetically predisposed animals, even after a relatively short period of exposure (1 month). The only exception to this hypo-connectivity state is the functional association between the striatal and prefrontal-cingulate networks, which increases after drinking, supporting evidence in human alcoholics.
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08:45-09:00, Paper FrAT3.4 | Add to My Program |
Difference of Alzheimer’s Disease Sub-Groups Using Two Features from Intensity Size Zone Matrix |
Lee, Seunghak | Sungkyunkwan Univ |
Park, Hyunjin | Sungkyunkwan Univ |
Keywords: Magnetic resonance imaging - MR neuroimaging, Image feature extraction, Brain image analysis
Abstract: Alzheimer’s disease (AD) is known as one of important diseases with world-wide impact. Unfortunately, we have not found the cause and treatment methods for AD. Magnetic resonance imaging (MRI) is an important research for AD research. Many recent studies focused on finding imaging biomarker associated with AD and mild cognitive impairment (MCI). Texture analysis jointly consider gray-level intensity and position of the voxels within a given region of interest (ROI). It can lead to better characterization of ROI than conventional approaches. We adopted one of the texture analysis methods called intensity size zone matrix (ISZM) to compare AD, late MCI (LMCI), early MCI (EMCI) and normal control (NC) subjects in both hemispheres of the hippocampus. As a result, we were able to distinguish among the sub-groups using the intensity variability feature and size zone variability feature computed from ISZM.
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09:00-09:15, Paper FrAT3.5 | Add to My Program |
Early Axonal Damage in Normal Appearing White Matter in Multiple Sclerosis: Novel Insights from Multi-Shell Diffusion MRI |
De Santis, Silvia | Univ. Miguel Hernandez De Elche |
Granberg, Tobias | Karolinska Inst |
Ouellette, Russell | Department of Radiology, Athinoula A. Martinos Center for Biomed |
Treaba, Constantina | Department of Radiology, Athinoula A. Martinos Center for Biomed |
Fan, Qiuyun | Department of Radiology, Athinoula A. Martinos Center for Biomed |
Herranz, Elena | Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA |
Mainero, Caterina | Department of Radiology, Athinoula A. Martinos Center for Biomed |
Toschi, Nicola | Univ. of Rome "Tor Vergata", Faculty of Medicine |
Keywords: Magnetic resonance imaging - MR neuroimaging, Brain image analysis, Magnetic resonance imaging - Diffusion tensor and diffusion spectrum imaging
Abstract: Conventional diffusion-weighted MR imaging techniques provide limited specificity in disentangling disease-related microstructural alterations involving changes in both axonal density and myelination. By simultaneously probing multiple diffusion regimens, multi-shell diffusion MRI is capable of increasing specificity to different tissue sub-compartments and hence separate different contributions to changes in diffusion-weighted signal attenuation. Advanced multi-shell diffusion models impose significant requirements on the amount of diffusion weighting (i.e. gradient coil performance) and angular resolution (i.e. in-scanner subject time), which commonly limits their applicability in a clinical setting. In this paper, we apply a high-b-value, high angular resolution multi-shell diffusion MRI protocol to a population of early multiple sclerosis (MS) patients and healthy controls. Through the Composite Hindered and Restricted Model of Diffusion (CHARMED) model, we extract indices for axonal density as well as parameters sensitive to myelin. We demonstrate increased sensitivity to microstructural changes in normal appearing white matter and in lesions in MS as compared to traditional models like DTI. These changes appear to be predominantly in axonal density, pointing towards the existence of axonal damage mechanisms in early MS.
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09:15-09:30, Paper FrAT3.6 | Add to My Program |
Brain Age Estimation from T1-Weighted Images Using Effective Local Features |
Fujimoto, Ryuichi | Tohoku Univ |
Ito, Koichi | Tohoku Univ |
Wu, Kai | South China Univ. of Tech |
Sato, Kazunori | Tohoku Univ |
Taki, Yasuyuki | Tohoku Univ |
Fukuda, Hiroshi | Tohoku Pharmaceutical Univ |
Aoki, Takafumi | Tohoku Univ |
Keywords: Magnetic resonance imaging - MR neuroimaging, Brain image analysis, Image feature extraction
Abstract: Statistical analysis using large-scale brain magnetic resonance (MR) image databases has examined that brain tissues have age-related morphological changes. The age of a subject can be estimated from the brain MR image by evaluating morphological changes with healthy aging. This paper proposes an age estimation method using local features of T1-weighted MR images. The brain local features are defined by volumes of brain tissues parcellated into 1,024 local regions defined by the automated anatomical labeling atlas. This paper also proposes the effective local feature selection method to improve the accuracy of age estimation. We evaluate the accuracy of the proposed method using 1,099 T1-weighted images from a Japanese MR image database. We also analyze effectiveness of each local region for age estimation and discuss its medical implication.
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FrAT4 Invited Session, Min Room |
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Body Sensor Networks – Molecules, Radio, and Machine Learning - I |
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Chair: Balasingham, Ilangko | Oslo Univ. Hospital and Norwegian Univ. of Science and Tech |
Co-Chair: Anzai, Daisuke | Nagoya Inst. of Tech |
Organizer: Balasingham, Ilangko | Oslo Univ. Hospital and Norwegian Univ. of Science and Tech |
Organizer: Anzai, Daisuke | Nagoya Inst. of Tech |
Organizer: Sugimachi, Masaru | Natl Cardio Center Res. Inst |
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08:00-08:15, Paper FrAT4.1 | Add to My Program |
Experimental Evaluation of 30 MHz Band Implant Communication Using Automatic Equalization Technique (I) |
Nomura, Kohei | Nagoya Inst. of Tech |
Anzai, Daisuke | Nagoya Inst. of Tech |
Wang, Jianqing | Nagoya Inst. of Tech |
Keywords: Implantable systems, Implantable technologies
Abstract: Body area networks (BANs) are attracting great attention in healthcare and medical applications, and capsule endoscope is one of implant BAN applications. For real-time image/video transmission in implant BAN, we previously developed an in-body transceiver at around 30 MHz with a bandwidth of 50 MHz. However, an implant channel can cause severe waveform distortion so that the communication performance gets deteriorated. Therefore, in this study we developed an automatic equalizer on the transceiver. Moreover, we evaluated its communication performance. The measurement result shows that our developed equalizer can largely improve the communication performance in the implant BAN channel.
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08:15-08:30, Paper FrAT4.2 | Add to My Program |
Development and Experimental Evaluation on Implant UWB-MIMO Transmission (I) |
Anzai, Daisuke | Nagoya Inst. of Tech |
Ohta, Masahiro | Nagoya Inst. of Tech |
Shimizu, Yuto | Naogya Inst. of Tech |
Balasingham, Ilangko | Oslo Univ. Hospital and Norwegian Univ. of Science And |
Wang, Jianqing | Nagoya Inst. of Tech |
Keywords: Wearable antennas and in-body communications, Implantable technologies, Implantable systems
Abstract: Implant ultra-wideband (UWB) communication has so far attracted a lot of attention as a promising technology of reliable and high-speed transmission for implantable devices. In this paper, we developed a multiple-input multiple-output (MIMO) transmission system to realize reliable implant UWB communication. Furthermore, we carried out an experiment with liquid phantom for evaluating the developed UWB-MIMO system. Our experimental results showed that the develop system achieved the bit error rate (BER) performance of 0.01 at sufficient transmission points inside the liquid phantom ensuring the high date rate of 66 Mbps.
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08:30-08:45, Paper FrAT4.3 | Add to My Program |
Wideband Phantoms of Different Body Tissues for Heterogeneous Models in Body Area Networks |
Castelló-Palacios, Sergio | Univ. Pol. De Valencia |
Garcia-Pardo, Concepcion | Univ. Pol. De Valencia |
Fornes-Leal, Alejandro | Univ. Pol. De Valencia |
Cardona, Narcis | Univ. Pol. De València |
Vallés-Lluch, Ana | Univ. Pol. De València |
Keywords: Wearable antennas and in-body communications, Implantable systems, Physiological monitoring - Instrumentation
Abstract: One of the key issues about wireless technologies is their interaction with the human body. The so-called internet of things will comprise many devices that will transmit either around or through the human body. These devices must be tested either in their working medium, when possible, or in the most realistic one. For this purpose, tissue-like phantoms are the best alternative to carry out realistic analyses of the performance of body area networks. In addition, they are the conventional way to certify the compliance of commercial standards by these devices. However, the number of phantoms that work in large bandwidths is limited in literature. This work aims at presenting chemical solutions that will be useful to prepare a variety of wideband tissue phantoms. Besides, the colon was mimicked in two ways, the healthy tissue and the malignant one, taking into account studies that relate changes on the relative permittivity with cancer. They were designed on the basis of acetonitrile in aqueous solutions as described in a previous work. Thus, many scenarios could be developed such as multilayers which imitate parts of the heterogeneous body.
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08:45-09:00, Paper FrAT4.4 | Add to My Program |
A Wireless Capsule Endoscopy Steering Mechanism Using Magnetic Field Platform |
Alsunaydih, Fahad Nasser | Monash Univ |
Redouté, Jean-Michel | Monash Univ |
Yuce, Mehmet | Monash Univ |
Keywords: New technologies and methodologies in medical robotics, Clinical robots
Abstract: In this paper, a new steering mechanism for wireless capsule devices is presented. The proposed system consists of a platform generating a magnetic field to direct and control the motion of a capsule. The platform contains an upper and a lower set of electromagnets. A permanent magnet is implanted inside the capsule to initiate the movement, which is set by the magnetic field delivered by the electromagnets. The total magnetic field at the capsule’s location is the sum of the contributions of each electromagnet. An experimental setup has been designed for testing and comparing between the performance of the capsule mobility in practice and simulations.
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09:00-09:15, Paper FrAT4.5 | Add to My Program |
A Swallowable Sensing Device Platform with Wireless Power Feeding and Chemical Reaction Actuator |
Nakamura, Ryota | Kobe Univ |
Izumi, Shintaro | Kobe Univ |
Kawaguchi, Hiroshi | Kobe Univ |
Ohta, Hidetoshi | Sapporo Orthopedics and Cardiovascular Hospital |
Yoshimoto, Masahiko | Kobe Univ |
Keywords: Implantable systems, Wearable antennas and in-body communications, Wearable body sensor networks and telemetric systems
Abstract: This paper presents a swallowable sensor device that can be ingested orally, later arriving to the stomach, where the device can indwell for a long term. It can be egested at any time after it is triggered using wireless communication. This device is able to indwell by using a silicone balloon in the gastrointestinal tract. The balloon is inflated inside the stomach by a chemical reaction, and it is deflated to egest the sensor device using an actuator with electrolysis of water. Energy for the actuator with electrolysis can be fed wirelessly. A Near Field Communication and flexible antenna are employed for the power feeding and wireless data communication. The device size can be minimized without performance degradation because of the flexible balloon and the flexible antenna.
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FrAT5 Minisymposium, Lee Room |
Add to My Program |
Opportunities and Challenges for Wearable Medical Devices |
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Chair: Park, Sung-Min | POSTECH |
Co-Chair: Namkoong, Kak | Samsung Advanced Inst. of Tech. Samsung Electronics Co., Ltd |
Organizer: Park, Sung-Min | POSTECH |
Organizer: Namkoong, Kak | Samsung Electronics |
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08:00-08:15, Paper FrAT5.1 | Add to My Program |
Investigating Acute Skin Barrier Disruption Using Reflectance NIR Spectroscopy (I) |
SHIN, Eui Seok | Samsung Advanced Inst. of Tech |
Lee, June-Young | Samsung Advanced Inst. of Tech |
Lee, Seung Jun | Samsung Advanced Inst. of Tech |
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08:15-08:30, Paper FrAT5.2 | Add to My Program |
Wearable MINDS: Cuffless Blood Pressure Monitoring (I) |
Zhang, Yuan-Ting | The Chinese Univ. of Hong Kong |
Ding, Xiao-Rong | The Chinese Univ. of Hong Kong |
Yan, Bryan P. | Prince of Wales Hospital, the Chinese Univ. of Hong Kong |
Liu, Jing | The Chinese Univ. of Hong Kong |
Su, Peng | The Chinese Univ. of Hong Kong |
Zhao, Ni | The Chinese Univ. of Hong Kong |
Keywords: Physiological monitoring - Instrumentation, Physiological monitoring - Modeling and analysis, Wearable sensor systems - User centered design and applications
Abstract: Using wearable, cuffless arterial blood pressure monitoring devices as examples, this talk will discuss the miniaturization, intelligence, networking, digitization, and standardization (MINDS) aspects of wearable medical devices. Specifically, some pulse transit time (PTT) based approaches including both machine learning methods and physiological modelling methods such as photoplethysmogram intensity ratio (PIR), multi-wavelength and multi-modal measurements will be examined for the improvement of cuffless blood pressure measurement accuracy. The focus of this talk will be placed on the studies of variabilities of blood pressure and its indicators. The application of physiological markers obtained from unobtrusive cuffless blood pressure measuring devices in the project of myocardial infarction and stroke screening and intervention of nations (MISSION) will be introduced with the emphasis on its integration with biomarkers and imaging markers for the early prediction of acute cardiovascular diseases.
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08:30-08:45, Paper FrAT5.3 | Add to My Program |
Optical Sensor for Non-Invasive Glucose Monitoring (I) |
So, Peter | MIT |
Kang, Jeon Woong | MIT |
Dasari, Ramachandra | MIT |
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FrAT6 Invited Session, Zworykin Room |
Add to My Program |
Single Protein Sensors and Actuators |
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Chair: LU, Zuhong | Southeast Univ |
Co-Chair: CHEN, ANTONY | Peking Univ. Coll. of Engineering, |
Organizer: LU, Zuhong | Southeast Univ |
Organizer: CHEN, ANTONY | Peking Univ. Coll. of Engineering, |
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08:00-08:15, Paper FrAT6.1 | Add to My Program |
Single Molecule High-Throughput Detection Platform for DNA Sequencing and Protein Machinery (I) |
He, Jiankui | South Univ. of Science and Tech. of China |
Keywords: Microfluidic applications
Abstract: Detecting the primary sequences for DNA and protein at single molecule level are at the frontier of genomics and proteomics research. In this presentation, I am going to talk about the single molecule DNA sequencing and then discuss the single molecule protein sequencing method.
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08:15-08:30, Paper FrAT6.2 | Add to My Program |
Real-Time Monitored Enzyme Catalysis Reaction Based on a Solid-State Nanopore (I) |
Liu,, Quanjun | Southeast Univ |
Tan, ShengWei | Southeast Univ |
Keywords: Micro- and nano-sensors, Electric fields - Tissue regeneration
Abstract: The solid state nanopore sensor as a high-throughput and low-cost technology can detect the enzyme catalytic reaction in a solution, it has ability to detect enzyme reaction in the nanoscale environment. In the present study, we used diameter ~28nm Si3N4 nanopore to detect the single horseradish peroxidase (HRP) molecule catalysis substrates and a real-time monitored enzyme catalysis substrates were investigated. This approach offers the potential for further development as studying gene expression, enzyme dynamics at the single-molecule level and quantitative test of small molecules.
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08:30-08:45, Paper FrAT6.3 | Add to My Program |
Mechanical Allostery of I-Domain-Containing Leukocyte Integrins (I) |
Mao, Debin | Inst. of Mechanics, Chinese Acad. of Sciences |
Zhang, Xiao | Inst. of Mechanics, Chinese Acad. of Sciences |
Lü, Shouqin | Inst. of Mechanics, Chinese Acad. of Sciences |
Long, Mian | Inst. of Mechanics, Chinese Acad. of Sciences |
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08:45-09:00, Paper FrAT6.4 | Add to My Program |
Spatio-Temporal Fluctuations of Single Protein Machine Investigated by Liquid Cell Transmission Electron Microscopy (I) |
LU, Zuhong | Southeast Univ |
Wang, Zunliang | Southeast Univ |
GE, Qinyu | Southeast Univ |
Tu, Jing | Southeast Univ |
Keywords: Microfluidic techniques, methods and systems, Microfluidic applications, Biomaterials - Chemical and electrochemical sensors
Abstract: Protein machines work in aqueous solutions, and conformational flexibility is a key feature for proper functioning. Liquid phase electron microscopy enables molecular imaging with high spatial and temporal resolutions, which gives the opportunity to directly observe the conformational dynamics of single protein machines in their hydrated state. Here we provide preliminary studies on single protein imaging in solution at room temperature and discuss the strategies undertaken in our laboratory to improve imaging quality and resolution.
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09:00-09:15, Paper FrAT6.5 | Add to My Program |
The Use of Photoactivated Localization Microscopy-Based Approaches to Decipher the Role of RNA in Retrovirus Assembly at Nanoscale Resolutions in Living Cells (I) |
CHEN, ANTONY | Peking Univ. Coll. of Engineering, |
Keywords: Micro- and nano-sensors, Nano-bio technology design, Micro- and nano-technology
Abstract: Gag is the main viral structural protein that orchestrates the generation of retroviral particles. To drive particle assembly, thousands of Gag monomers must coalesce within a larger pool of host cellular proteins to form a highly-ordered Gag multimer at the plasma membrane (PM). To date, it is widely accepted that this process is mediated by Gag binding to long-stranded RNAs, including viral and cellular RNAs, which serve as scaffolds upon which Gag binds nonspecifically and then multimerizes. However, how Gag interacts with the scaffolding RNAs during the assembly process still remains an open question. We plan to employ super-resolution imaging techniques including photoactivated localization microscopy (PALM) and pair correlation PALM, combined with single-molecule FRET (smFRET), to map out the spatial organization, stoichiometry and dynamics of the interactions between Gag and RNAs at the single-molecule level. We hope these findings can provide new insights into the role of RNA in retroviral biogenesis in host cells, benefiting the design of novel therapeutics against retrovirus transmission and infectivity.
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FrAT7 Oral Session, Herrick Room |
Add to My Program |
Neurological Disorders I |
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Chair: Nguyen, Hung T. | Univ. of Tech. Sydney |
Co-Chair: Joo, Segyeong | Asan Medical Center, Univ. of Ulsan Coll. Ofmedicine |
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08:00-08:15, Paper FrAT7.1 | Add to My Program |
Detection of Turning Freeze in Parkinson’s Disease Based on S-Transform Decomposition of EEG Signals |
Ly, Quynh Tran | Univ. of Tech. Sydney |
Handojoseno, Aluysius Maria Ardi | Univ. of Tech. Sydney |
Gilat, Moran | Parkinson’s Disease Res. Clinic, Brain and Mind Res. Ins |
Chai, Rifai | Univ. of Tech. Sydney |
Ehgoetz Martens, Kaylena | Univ. of Sydney |
Georgiades, Matthew | Univ. of Sydney |
Naik, Ganesh R | Univ. of Tech. Sydney |
Tran, Yvonne | Univ. of Tech. Sydney |
Lewis, Simon J.G. | Parkinson’s Disease Res. Clinic, Brain and Mind Res. Ins |
Nguyen, Hung T. | Univ. of Tech. Sydney |
Keywords: Neurological disorders
Abstract: Freezing of Gait (FOG) is a highly debilitating and poorly understood symptom of Parkinson’s disease (PD), causing severe immobility and decreased quality of life. Turning Freezing (TF) is known as the most common sub-type of FOG, also causing the highest rate of falls in PD patients. During a TF, the feet of PD patients appear to become stuck whilst making a turn. This paper presents an electroencephalography (EEG) based classification method for detecting turning freezing episodes in six PD patients during Timed Up and Go Task experiments. Since EEG signals have a time-variant nature, time-frequency Stockwell Transform (S-Transform) techniques were used for feature extraction. The EEG sources were separated by means of independent component analysis using entropy bound minimization (ICA-EBM). The distinctive frequency-based features of selected independent components of EEG were extracted and classified using Bayesian Neural Networks. The classification demonstrated a high sensitivity of 84.2%, a specificity of 88.0% and an accuracy of 86.2% for detecting TF. These promising results pave the way for the development of a real-time device for detecting different sub-types of FOG during ambulation.
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08:15-08:30, Paper FrAT7.2 | Add to My Program |
Detection of Gait Initiation Failure in Parkinson’s Disease Based on Wavelet Transform and Support Vector Machine |
Ly, Quynh Tran | Univ. of Tech. Sydney |
Handojoseno, Aluysius Maria Ardi | Univ. of Tech. Sydney |
Gilat, Moran | Parkinson’s Disease Res. Clinic, Brain and Mind Res. Ins |
Chai, Rifai | Univ. of Tech. Sydney |
Ehgoetz Martens, Kaylena | Univ. of Sydney |
Georgiades, Matthew | Univ. of Sydney |
Naik, Ganesh R | Univ. of Tech. Sydney |
Tran, Yvonne | Univ. of Tech. Sydney |
Lewis, Simon J.G. | Parkinson’s Disease Res. Clinic, Brain and Mind Res. Ins |
Nguyen, Hung T. | Univ. of Tech. Sydney |
Keywords: Neurological disorders
Abstract: Gait initiation Failure (GIF) is the situation in which patients with Parkinson’s disease (PD) feel as if their feet get “stuck” to the floor when initiating their first steps. GIF is a sub-type of Freezing of Gait (FOG) and often leads to falls and related injuries. Understanding of neurobiological mechanisms underlying GIF has been limited by difficulties in eliciting and objectively characterizing such gait phenomena in the clinical setting. Studies investigating the effects of GIF on brain activity using EEG offer the potential to study such behavior. In this study, we present a novel methodology where wavelet transform was used for feature extraction and Support Vector Machine for classifying GIF events in five patients with PD and FOG. To deal with the large amount of EEG data, a Principal Component Analysis (PCA) was applied to reduce the data dimension from 15 EEG channels into 6 principal components (PCs), retaining 93% of the information. Independent Component Analysis using Entropy Bound Minimization (ICA-EBM) was applied to 6 PCs for source separation with the aim of improving detection ability of GIF events as compared to the normal initiation of gait (Good Starts). The results of this analysis demonstrated the correct identification of GIF episodes with an 83.1% sensitivity, 89.5% specificity and 86.3% accuracy. These results suggest that our proposed methodology is a promising non-invasive approach to improve GIF detection in PD and FOG.
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08:30-08:45, Paper FrAT7.3 | Add to My Program |
Posturography Stability Score Generation for Stroke Patient Using Kinect: Fuzzy Based Approach |
Mazumder, Oishee | Tata Consultance Services |
Chakravarty, Kingshuk | Tata Consultancy Services Ltd |
Chatterjee, Debatri | TCS Innovation Lab |
Sinha, Aniruddha | Tata Consultancy Services Ltd |
Das, Abhijit | Inst. of Neurosciences Kolkata |
Keywords: Neurological disorders - Stroke, Human performance
Abstract: Aim of this paper is to formulate a posturography stability score for stroke patients using fuzzy logic. Postural instability is one of the prominent symptoms of stroke, dementia, parkinsons disease, myopathy, etc. and is the major precursor of fall. Conventional scoring techniques used to assess postural stability require manual intervention and are dependent on live interaction with physiotherapist. We propose a novel scoring technique to calculate static stability of a person using posturography features acquired by Kinect sensor, which do not require any manual intervention or expert guidance, is cost effective and hence are ideal for tele rehabilitation purpose. Stability analysis is done during Single Limb Stance (SLS) exercise. Kinect sensor is used to calculate three features, naming SLS duration, vibration index, calculated from mean vibration of twenty joints and sway area of Centre of Mass (CoM). Based on the variation of these features, a fuzzy rule base is generated which calculates a static stability score. One way analysis of variance (Anova) between a group of stroke population and healthy individuals under study validates the reliability of the proposed scorer. Generated fuzzy score are comparable with standard stability scorer like Berg Balance scale and fall risk assessment tool like Johns Hopkins scale. Stability score, besides providing an index of overall stability can also be used as a fall predictability index.
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08:45-09:00, Paper FrAT7.4 | Add to My Program |
Automated Epileptiform Spike Detection Via Affinity Propagation-Based Template Matching |
Thomas, John | Nanyang Tech. Univ |
Jing, Jin | Nanyang Tech. Univ |
Dauwels, Justin | NTU |
Cash, Sydney | Massachusetts General Hospital |
Westover, Brandon | Massachusetts General Hospital |
Keywords: Neurological disorders - Diagnostic and evaluation techniques, Neural signal processing, Neurological disorders - Epilepsy
Abstract: Interictal epileptiform spikes are the key diagnostic biomarkers for epilepsy. The clinical gold standard of spike detection is visual inspection performed by neurologists. This is a tedious, time-consuming, and expert-centered process. The development of automated spike detection systems is necessary in order to provide a faster and more reliable diagnosis of epilepsy. In this paper, we propose an efficient template matching spike detector based on a combination of spike and background waveform templates. We generate a template library by clustering a collection of spikes and background waveforms extracted from a database of 50 patients with epilepsy. We benchmark the performance of five clustering techniques based on the receiver operating characteristic (ROC) curves. In addition, background templates are integrated with existing spike templates to improve the overall performance. The affinity propagation-based template matching system with a combination of spike and background templates is shown to outperform the other four conventional methods with the highest area-under-curve (AUC) of 0.953.
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09:00-09:15, Paper FrAT7.5 | Add to My Program |
A New Infarction Detection Method Based on Heart Rate Variability in Rat Middle Cerebral Artery Occlusion Model |
Kodama, Tomonobu | The Jikei Univ. School of Medicine |
Kamata, Keisuke | Kyoto Univ |
Fujiwara, Koichi | Kyoto Univ |
Kano, Manabu | Kyoto Univ |
Yamakawa, Toshitaka | Kumamoto Univ |
Yuki, Ichiro | The Jikei Univ. School of Medicine |
Murayama, Yuichi | Jikei Univ. School of Medicine |
Keywords: Neurological disorders - Stroke, Brain physiology and modeling, Neurological disorders - Treatment methodologies
Abstract: Objective: The present study proposes a cerebral infarction detection algorithm based on heart rate variability (HRV). Methods: It has been reported that infarction affects HRV. Therefore, infarction could be detected at an acute stage by monitoring HRV. This study uses multivariate statistical process control (MSPC), which is a well-known anomaly monitoring method. HRV data shortly after infarction onsets are collected by using the middle cerebral artery occlusion (MCAO) model in rats. This study prepares 11 MCAO-operated rats and 11 sham-operated rats. Three sham-operated rats’ data are used for model construction of MSPC, and the other 19 rats’ data are used for its validation. Results: The sensitivity and specificity of the proposed algorithm were 82 % and 75 %, respectively. Conclusion: An infarction onset could be detected at an acute stage by monitoring HRV.
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09:15-09:30, Paper FrAT7.6 | Add to My Program |
Stroke Lesion Location Influences the Decoding of Movement Intention from EEG |
López-Larraz, Eduardo | Univ. of Tübingen |
Ray, Andreas Markus | Tuebingen Univ |
da Cruz Figueiredo, Thiago | Univ. of Tübingen |
Bibián, Carlos | Univ. Tübingen |
Birbaumer, Niels | Eberhard-Karls-Univ |
Ramos-Murguialday, Ander | Eberhard Karls Univ. of Tubingen/TECNALIA |
Keywords: Neurorehabilitation, Brain-computer/machine interface, Neurological disorders - Stroke
Abstract: Recent studies have demonstrated the efficacy of brain-machine interfaces (BMI) for motor rehabilitation after stroke, especially for those patients with severe paralysis. However, a cerebro-vascular accident can affect the brain in many different manners, and damage in various areas can lead to similar or equal motor deficits. The location of the insult influences the way the brain activates when moving or attempting to move a paralyzed limb. Since the essence of a rehabilitative BMI is to precisely decode motor commands from the brain, it is crucial to characterize how lesion location affects the measured signals and if and how it influences BMI performance. This paper compares the performances of an electroencephalography (EEG)-based movement intention decoder in two groups of severely paralyzed chronic stroke patients: 14 with subcortical lesions and 14 with mixed (i.e., cortical and subcortical) lesions. We show that the lesion location influences the performance of the BMI when decoding the movement attempts of the paretic arm. The obtained results underline the need of further developments for a better individualization of BMI-based rehabilitative therapies for stroke patients.
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FrAT8 Oral Session, Schwan Room |
Add to My Program |
Brain Image Analysis I |
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Chair: Hu, Qingmao | Shenzhen Inst. of Advanced Tech. Chinese Acad. of Sciences |
Co-Chair: Park, Hyunjin | Sungkyunkwan Univ |
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08:00-08:15, Paper FrAT8.1 | Add to My Program |
Automated Subdural Hematoma Segmentation for Traumatic Brain Injured (TBI) Patients |
Farzaneh, Negar | Univ. of Michigan |
Soroushmehr, S.M.Reza | Univ. of Michigan, Ann Arbor |
Williamson, Craig | Univ. of Michigan |
Jiang, Cheng | Univ. of Michigan |
Srinivasan, Ashok | Univ. of Michigan |
Bapuraj, Jayapalli Rajiv | Univ. of Michigan |
Ward, Kevin | Univ. of Michigan |
Korley, Frederick K | Univ. of Michigan |
Najarian, Kayvan | Univ. of Michigan - Ann Arbor |
Keywords: Brain image analysis, Image segmentation, Image feature extraction
Abstract: Traumatic brain injury is a serious public health problem in the U.S. contributing to a large portion of permanent disability. However, its early management and treatment could limit the impact of the injury, save lives and reduce the burden of cost for patients as well as healthcare systems. Subdural hematoma is one of the most common types of TBI, which its visual detection and quantitative evaluation are time consuming and prone to error. In this study, we propose a fully automated machine learning based approach for 3D segmentation of convexity subdural hematomas. Textural, statistical and geometrical features of sample points from intracranial region are extracted based on head Computed Tomography (CT) images. Then, a tree bagger classifier is implemented to classify each pixel as hematoma or no-hematoma. Our method yields sensitivity, specificity and area under the receiver operating curve (AUC) of 85.02%, 73.74% and 0.87 respectively.
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08:15-08:30, Paper FrAT8.2 | Add to My Program |
Compartmental Sparse Feature Selection Method for Alzheimer’s Disease Identification |
Liu, Yan | Univ. of Chinese Acad. of Sciences |
Wang, Ling | Univ. of Electronic Science and Tech. of China |
zeng, xiangzhu | Peking Univ. Third Hospital, Beijing, China |
Wang, Zheng | Capital Univ. of Medical Sciences |
Gao, Yajun | The General Hospital of Petroleum Administration of North China |
Wang, Qiuyue | The General Hospital of Petroleum Administration of North China |
Keywords: Brain image analysis, Image classification, Image feature extraction
Abstract: For high-dimensional magnetic resonance imaging (MRI) data, many feature selection methods have been proposed to reduce feature dimension in the study of computer-aided Alzheimer’s disease (AD) diagnosis. This paper presents a compartmental sparse feature selection method used for AD identification. Based on the derived atlas-based regions-of-interest (ROIs) of brain, the proposed method partitioned the T1-weighted MRI data into several compartments. It performs feature selection and classification compartmentally according to the local feature dimension estimation and local feature selection using sparse principal component analysis (SPCA) method followed with elastic-net logistic regression (ENLR) classifier. Experimental results showed that the proposed method improves the classification performance for small ROIs with high computational efficiency.
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08:30-08:45, Paper FrAT8.3 | Add to My Program |
Low Grade Glioma Growth Modeling Considering Chemotherapy and Radiotherapy Effects from Magnetic Resonance Images |
Elazab, Ahmed | Shenzhen Inst. of Advanced Tech |
Bai, Hongmin | Department of Neurosurgery, Guangzhou General Hospital of Guangz |
Zhang, Xiaodong | Shenzhen Inst. of Advanced Tech. Chinese Acad. of S |
Hu, Qingmao | Shenzhen Inst. of Advanced Tech. Chinese Acad. of S |
Keywords: Brain image analysis, Magnetic resonance imaging - Contrast-enhanced dynamic MRI, Multiscale image analysis
Abstract: Studying tumor growth using mathematical mod-els from magnetic resonance (MR) images is an important ap-plication that is believed to play a major role in cancer treatment by predicting tumor evolution, quantifying the response to therapy, and treatment planning. Reaction diffusion is the most popular model because of its simplicity and consistency with the biological growth process. However, most of the current growth models focus on presurgical images and likely without treatment. In this paper, we propose a new reaction diffusion model to consider the chemotherapy and radiotherapy effects on the tumor growth modelling for patients with low grade glioma. The proposed model does not consider the tensor information from diffusion tensor imaging. Instead it uses a weighted parameter to promote higher diffusivity in white matter. The radiotherapy and chemotherapy effects are considered as a loss terms in the proposed model. The preliminary results of the proposed model on 2 MR images show that, our model can effectively simulate tumor growth with high accuracies when treatments are ad-ministrated to low grade glioma patients.
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08:45-09:00, Paper FrAT8.4 | Add to My Program |
Classification of Low-Grade and High-Grade Glioma Using Multi-Modal Image Radiomics Features |
Cho, Hwan-ho | Sungkyunkwan Univ |
Park, Hyunjin | Sungkyunkwan Univ |
Keywords: Brain image analysis, Magnetic resonance imaging - MR neuroimaging, Magnetic resonance imaging - Contrast-enhanced dynamic MRI
Abstract: Gliomas are primary brain tumors arising from glial cells. Gliomas can be classified into different histopathologic grades according to World Health Oraganization (WHO) grading system which represents malignancy. In this paper, we present a method to predict the grades of Gliomas using Radiomics imaging features. MICCAI Brain Tumor Segmentation Challenge (BRATs 2015) training data, its segmentation ground truth and the ground truth labels were used for this work. 45 radiomics features based on histogram, shape and gray-level co-occurrence matrix (GLCM) were extracted from each FLAIR, T1, T1-Contrast, T2 image to quantify the property of Gliomas. Significant features among 180 features were selected through L1-norm regularization (LASSO). Based on LASSO coefficient and selected feature values, we computed a LASSO score and gliomas were classified into low-grade glimoa (LGG) or high-grade glimoa (HGG) through logistic regression. Classification result was validated by a 10-fold cross validation. Our method achieved accuracy of 0.8981, sensitivity of 0.8889, specificity of 0.9074, and area under the curve (AUC) = 0.8870.
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09:00-09:15, Paper FrAT8.5 | Add to My Program |
Contribution to Speech Development of the Right Anterior Putamen Revealed with Multivariate Tensor-Based Morphometry |
Vlasova, Roza | CIBORG Lab, Department of Radiology, Children's Hospital Los Ang |
Wang, Yalin | Arizona State Univ |
Dirks, Holly | Brown Univ |
Dean, Douglas | Univ. of Wisconsin-Madison |
O’Muircheartaigh, Jonathan | Brown Univ |
Gonzalez, Sara | CIBORG Lab, Department of Radiology, Children's Hospital Los Ang |
Nguyen, Binh Kien | CIBORG Lab, Department of Radiology, Children's Hospital Los Ang |
Nelson, Marvin | Univ. of Southern California and Keck School of Medicine, C |
Deoni, Sean | Univ. of Colorado |
Lepore, Natasha | Univ. of Southern California / Children's Hospital Los Ange |
Keywords: Brain image analysis, Magnetic resonance imaging - MR neuroimaging
Abstract: In our previous study, we suggested that the difference between tensor-based metrics in the anterior part of the right putamen between 21 and 18 months age groups associated with speech development during this ages. Here we used a correlational analysis between verbal scores and determinant of the Jacobian matrix to confirm our hypothesis. Significant correlations in the anterior part of the right putamen between verbal scores and surface metric were revealed in the 18 and 21 age groups.
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FrAT9 Minisymposium, Plonsey Room |
Add to My Program |
Neural Prosthetic Devices Usable for Animal and Clinical Studies, in Asian
Countries |
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Chair: Hayashida, Yuki | Osaka Univ |
Co-Chair: Kim, Kyung Hwan | Yonsei Univ |
Organizer: Hayashida, Yuki | Osaka Univ |
Organizer: Kim, Kyung Hwan | Yonsei Univ |
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08:00-08:15, Paper FrAT9.1 | Add to My Program |
The Brain Mapping System Design with Closed-Loop Stimulation Capability for Seizure Onset Region Mapping and Control for Epileptic Patients (I) |
Cheng, Cheng-Hsiang | National Chiao Tung Univ |
Ker, Ming-Dou | National Chiao Tung Univ |
Lee, Chen-Yi | National Chiao Tung Univ |
Hsin, Yue-Loong | Chung Shan Medical Univ |
Liang, Sheng-Fu | National Cheng Kung Univ |
Shaw, Fu-Zen | National Cheng Kung Univ |
Wu, Chung-Yu | National Chiao Tung Univ |
Keywords: Neural stimulation, Neurological disorders - Diagnostic and evaluation techniques, Neurological disorders - Epilepsy
Abstract: This paper presents a novel brain mapping system for seizure onset region identification and control in treating epileptic seizure of patients. The proposed system consists of a closed-loop seizure control system-on-chip (SoC) and a control panel with graphical user interface. It can be used to identify the seizure onset brain regions and determine the most suitable parameters for a closed-loop cortical stimulation for epileptic patients.
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08:15-08:30, Paper FrAT9.2 | Add to My Program |
Implantable Optoelectronic Devices for Measurement and Control of Neural Functions (I) |
Sasagawa, Kiyotaka | Nara Inst. of Science and Tech |
Haruta, Makito | Nara Inst. of Science and Tech |
Yamaguchi, Takahiro | Nara Inst. of Science and Tech |
Fujimoto, Koki | Nara Inst. of Science and Tech |
Sunaga, Yoshinori | Nara Inst. of Science and Tech |
Ohta, Yasumi | Nara Inst. of Science and Tech |
Noda, Toshihiko | Nara Inst. of Science and Tech |
Tokuda, Takashi | Nara Inst. of Science and Tech |
Ohta, Jun | Nara Inst. of Science and Tech |
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08:30-08:45, Paper FrAT9.3 | Add to My Program |
Wireless Device System for Multi-Channel Intra-Cortical Microstimulations ~Evaluation with Animal Studies in Vivo (I) |
Hayashida, Yuki | Osaka Univ |
Keywords: Neural interfaces - Implantable systems, Sensory neuroprostheses, Neural stimulation
Abstract: Recently, we have been developing a multi-channel intra-cortical microstimulation system, which comprises a pair of intra- and extra-body devices equipped with wireless data communication and power transmission. The intra-body device can drive one or up to sixty four of a microampere-range 64-channel stimulator chip we developed. Thus, the system is expected to be applicable to various neural prostheses. However, in order to evaluate the operations of such a prosthetic device, animal studies in vivo would be inevitable. Thus, we utilized the in-vivo voltage-sensitive dye imaging technique to examine spatio-temporal neural responses to microstimulations generated by the wireless device system. The experimental results demonstrated a usefulness of our setup, in which quantitative relationships between the stimuli and the corresponding neural responses can be investigated.
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08:45-09:00, Paper FrAT9.4 | Add to My Program |
Neural Signal Processing for Closed-Loop Neuromodulation (I) |
Kim, Kyung Hwan | Yonsei Univ |
Keywords: Neural signal processing, Neural stimulation, Neurological disorders
Abstract: The purpose of this presentation is to provide an overview of neural signal processing techniques for closed-loop neuromodulation. After illustrating overall structure of closed-loop neuromodulation systems, the techniques for the stimulus artifact removal will be explained, and the methods for neural state monitoring and biomarker extraction will be described. Finally, the current status of neuromodulation based on neural signal processing will be presented in detail. Closed-loop neuromodulation system automatically adjusts stimulation parameters based on the brain response in real time. Adequate tools for signal sensing and signal processing can be used to obtain meaningful biomarkers reflecting the state of neural systems. Especially, an appropriate neural signal processing technique can optimize the details of stimulation for effective treatment of target disease. Neural signal-based biomarkers reflecting the pathophysiological statuses of patients are essential for closed-loop neuromodulation, and they should be developed from an understanding of the relationship between clinical states and neural signals.
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09:00-09:15, Paper FrAT9.5 | Add to My Program |
A Multi-Channel Neural Recording ASIC Chip for a Fully Implantable Wireless BMI System (I) |
Kameda, Seiji | Osaka Univ |
Ando, Hiroshi | NICT |
Kamata, Takatsugu | Osaka Univ |
Imajo, Kaoru | Nihon Kohden Corp |
Suzuki, Katsuyoshi | NIHON KOHDEN Corp |
Suzuki, Takafumi | National Inst. of Information Andcommunicationstechnology |
Hirata, Masayuki | Osaka Univ. Medical School |
Keywords: Brain-computer/machine interface, Neural interfaces - Implantable systems, Motor neuroprostheses
Abstract: The brain-machine interface (BMI) is a new method for man-machine interfaces, which enables us to control machines and to communicate with others only using brain signals. In the present study, we fabricated a multi-channel neural recording ASIC chip for a fully implantable wireless BMI system. The chip has 32 neural recording channels and the input referred noise is below 3 µVpp. In addition, we developed a prototype fully implantable wireless BMI system containing the ASIC chips. To confirm the proper performance as neural recording device, the BMI system was applied to in vivo animal experiment.
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09:15-09:30, Paper FrAT9.6 | Add to My Program |
Design of a Novel Epiretinal Microelectrode Array for Improving Retinal Stimulation Spatial Resolution by Computational Modeling (I) |
Li, Liming | Shanghai Jiao Tong Univ |
Lyu, Qing | Shanghai Jiao Tong Univ |
Chen, Yao | Shanghai Jiao Tong Univ |
Chai, Xinyu | Shanghai JiaoTong Univ |
Keywords: Sensory neuroprostheses - Visual, Neural stimulation, Neurorehabilitation
Abstract: Despite the rapid development of retinal prostheses, subjects implanted with retinal prosthesis have reported a low visual acuity of prosthetic vision. A possible approach for improving visual acuity is to utilize electric field modulation technology to produce virtual electrodes. This study designed a novel epiretinal stimulating electrode array and explored its feasibility of producing controllable virtual electrodes through computational modeling. According to the simulation results, our designed electrode array could produce virtual electrodes with the use of current steering stimulation strategy, and the site of virtual electrodes could be controlled two-dimensionally. This study may provide support for the application of virtual electrodes in epiretinal prosthesis in the future for increasing the visual acuity of prosthetic vision.
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FrAT10 Oral Session, Schmitt Room |
Add to My Program |
General and Theoretical Informatics - Machine Learning I |
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Chair: Kim, Yongwook Bryce | Massachusetts Inst. of Tech |
Co-Chair: Ikeda, Kazushi | Nara Inst. of Science and Tech |
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08:00-08:15, Paper FrAT10.1 | Add to My Program |
Collision Frequency Locality-Sensitive Hashing for Prediction of Critical Events |
Kim, Yongwook Bryce | Massachusetts Inst. of Tech |
Hemberg, Erik | Mit Csail |
O'Reilly, Una-May | Massachusetts Inst. of Tech |
Keywords: General and theoretical informatics - Machine learning, General and theoretical informatics - Predictive analytics, General and theoretical informatics - Supervised learning method
Abstract: We present a fast, efficient method to predict future critical events for a patient. The prediction method is based on retrieving and leveraging similar waveform trajectories from a large medical database. Locality-sensitive hashing (LSH), our theoretical foundation, is a model-free, sub-linear time, approximate search method enabling a fast retrieval of a nearest neighbor set for a given query. We propose a new variant of LSH, namely Collision Frequency LSH (CFLSH), to further improve the prediction accuracy without sacrificing any speed. The key idea is that the more frequently an element and a query collide across multiple LSH hash tables, the more similar they are. Unlike the standard LSH which only utilizes the linear distance calculation, in CFLSH, the short-listing step from a pool of pre-selected candidates filtered by hash functions to the final nearest neighbor set relies upon the frequency of collision along with distance information. We evaluate CFLSH versus the standard LSH using the L1 and cosine distances, for predicting acute hypotensive episodes on arterial blood pressure time series data extracted from the MIMIC II database. Our results show that CFLSH for the L1 distance has a higher prediction accuracy and further accelerates the sub-linear querying time obtained by the standard LSH.
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08:15-08:30, Paper FrAT10.2 | Add to My Program |
Optimized Automatic Sleep Stage Classification Using the Normalized Mutual Information Feature Selection (NMIFS) Method |
Cho, Dongrae | Gwangju Inst. of Science and Tech |
Lee, Boreom | Gwangju Inst. of Science and Tech. (GIST) |
Keywords: General and theoretical informatics - Machine learning, General and theoretical informatics - Supervised learning method, Bioinformatics - Bioinformatics for health monitoring
Abstract: Sleep is a very important physiological phenomenon for recovery of physical and mental fatigue. Recently, there has been a lot of interest in the quality of sleep and the research is actively under way. In particular, it is important to have a repetitive and regular sleep cycle for good sleep. However, it takes a lot of time to determine sleep stages using physiological signals by experts. In this study, we constructed an optimized classifier based on normalized mutual information feature selection (NMIFS) and kernel based extreme learning machine (K-ELM), and total 4 sleep stages (Awake, weak sleep (stage1+stage2), deep sleep(stage3+stage4) and rapid eye movement (REM)) were automatically classified. As a results, the average of the accuracy obtained by proposed method (NMIFS+K-ELM) is 2~3% higher than that of simple method (K-ELM).
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08:30-08:45, Paper FrAT10.3 | Add to My Program |
Application of SsVGMM to Medical Data - Classification with Novelty Detection |
Yang, Fan | Nara Inst. of Science and Tech |
Soriano, Jaymar | Nara Inst. of Science and Tech |
Kubo, Takatomi | Nara Inst. of Science and Tech |
Ikeda, Kazushi | Nara Inst. of Science and Tech |
Keywords: General and theoretical informatics - Machine learning, General and theoretical informatics - Pattern recognition, Health Informatics - Knowledge discovery and management
Abstract: There is a huge demand to apply classification in medical analysis. A traditional classifier requires having training samples from each class. However, in reality, it is possible that the testing set may include classes that are not in the training set. This inevitably causes an issue: data from undefined class will be assigned to predefined classes. To tackle this, we propose a semi-supervised variational Gaussian mixture model to perform multi-class classification with novelty detection. Comparing to some popular novelty detection methods, we demonstrate that it gets better performance on a thyroid disease data, by generating the distribution of predefined classes and undefined class, without explicitly setting a threshold.
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08:45-09:00, Paper FrAT10.4 | Add to My Program |
Ensemble Transfer Learning for Alzheimer’s Disease Diagnosis |
Colbaugh, Richard | Periander Ltd |
Glass, Kristin | Periander Ltd |
Gallegos, Gil | New Mexico Highlands Univ |
Keywords: General and theoretical informatics - Machine learning, General and theoretical informatics - Predictive analytics
Abstract: There is considerable interest in developing inexpensive, nonintrusive diagnostic tests for Alzheimer’s disease (AD), in the hope these tests will facilitate early diagnosis and support design of effective treatments. While tests based on blood-borne biomarkers such as microRNAs have shown promise, work to date indicates these tests often do not generalize well: diagnostic models derived for one patient group are not accurate when applied to a new cohort. This paper presents a novel ensemble-based transfer learning methodology which induces models that provide accurate diagnoses across distinct patient groups without retraining. The algorithm combines information from supervised ensemble learning and unsupervised ensemble clustering to enable robust transfer learning. The efficacy of the approach is illustrated through a case study involving microRNA-based AD diagnosis. In this test, we use our algorithm to learn a diagnostic model on data from one patient group and then apply the model to a different target group, obtaining diagnostic accuracy which actually exceeds that of a state-of-the-art model trained directly on the target group.
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09:00-09:15, Paper FrAT10.5 | Add to My Program |
Learning about Individuals’ Health from Aggregate Data |
Colbaugh, Richard | Periander Ltd |
Glass, Kristin | Periander Ltd |
Keywords: General and theoretical informatics - Machine learning, General and theoretical informatics - Algorithms, General and theoretical informatics - Computational disease profiling
Abstract: There is growing awareness that user-generated social media content contains valuable health-related information and is more convenient to collect than typical health data. For example, Twitter has been employed to predict aggregate-level outcomes, such as regional rates of diabetes and child poverty, and to identify individual cases of depression and food poisoning. Models which make aggregate-level inferences can be induced from aggregate data, and consequently are straightforward to build. In contrast, learning models that produce individual-level (IL) predictions, which are more informative, usually requires a large number of difficult-to-acquire labeled IL examples. This paper presents a new machine learning method which achieves the best of both worlds, enabling IL models to be learned from aggregate labels. The algorithm makes predictions by combining unsupervised feature extraction, aggregate-based modeling, and optimal integration of aggregate-level and IL information. Two case studies illustrate how to learn health-relevant IL prediction models using only aggregate labels, and show that these models perform as well as state-of-the-art models trained on hundreds or thousands of labeled individuals.
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09:15-09:30, Paper FrAT10.6 | Add to My Program |
Comparing Deep Neural Network and Other Machine Learning Algorithms for Stroke Prediction in a Large-Scale Population-Based Electronic Medical Claims Database |
Hung, Chen-Ying | National Tsing Hua Univ |
Chen, Wei-Chen | Department of Electrical Engineering, National Tsing Hua Univ |
Lai, Po-Tsun | Department of Electrical Engineering, National Tsing Hua Univ |
Lin, Ching-Heng | Department of Medical Res. Taichung Veterans General Hospit |
Lee, Chi-Chun | National Tsing Hua Univ |
Keywords: Health Informatics - Electronic health records, General and theoretical informatics - Predictive analytics, General and theoretical informatics - Machine learning
Abstract: Electronic medical claims (EMCs) can be used to accurately predict the occurrence of a variety of diseases, which can contribute to precise medical interventions. While there is a growing interest in the application of machine learning (ML) techniques to address clinical problems, the use of deep-learning in healthcare have just gained attention recently. Deep learning, such as deep neural network (DNN), has achieved impressive results in the areas of speech recognition, computer vision, and natural language processing in recent years. However, deep learning is often difficult to comprehend due to the complexities in its framework. Furthermore, this method has not yet been demonstrated to achieve a better performance comparing to other conventional ML algorithms in disease prediction tasks using EMCs. In this study, we utilize a large population-based EMC database of around 800,000 patients to compare DNN with three other ML approaches for predicting 5-year stroke occurrence. The result shows that DNN and gradient boosting decision tree (GBDT) can result in similarly high prediction accuracies that are better compared to logistic regression (LR) and support vector machine (SVM) approaches. Meanwhile, DNN achieves optimal results by using lesser amounts of patient data when comparing to GBDT method.
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FrAT11 Oral Session, Greatbatch Room |
Add to My Program |
Cardiovascular Variability |
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Chair: BuSha, Brett | The Coll. of New Jersey |
Co-Chair: Lee, Boreom | Gwangju Inst. of Science and Tech. (GIST) |
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08:00-08:15, Paper FrAT11.1 | Add to My Program |
Evaluating the Association between Cardiac and Peripheral Resistance Arms of the Baroreflex |
Porta, Alberto | Univ. Degli Studi Di Milano |
Bari, Vlasta | IRCCS Pol. San Donato |
Ranuzzi, Giovanni | Department of Cardiothoracic, Vascular Anesthesia and Intensive |
De Maria, Beatrice | IRCCS Fondazione Salvatore Maugeri, Milano |
Malacarne, Mara | Dipartimento Di Biotecnologie Mediche E Medicina Traslazionale, |
Pagani, Massimo | Univ. Degli Studi Di Milano |
Lucini, Daniela | Univ. Degli Studi Di Milano |
Keywords: Cardiovascular regulation - Baroreflex, Cardiovascular regulation - Autonomic nervous system, Cardiovascular and respiratory signal processing - Heart Rate and Blood Pressure Variability
Abstract: The study proposes an extension of cardiac baroreflex (cBR) sequence analysis, traditionally performed over spontaneous fluctuations of heart period and systolic arterial pressure, to typify peripheral resistance baroreflex (prBR) from spontaneous variations of peripheral resistances and diastolic arterial pressure. The prBR baroreflex sensitivity (BRSprBR) and percentage of prBR sequences (SEQ%prBR) were computed along with analogous quantities assessed over cBR (i.e. BRScBR and SEQ%cBR). The cBR and prBR were typified in healthy subjects at rest (REST) and during light bicycle ergometer exercise at 10 percent of the maximal effort (EXE). Both cBR and prBR were affected by EXE: indeed, BRScBR and SEQ%prBR were significantly reduced. Moreover, while BRScBR and BRSprBR were not significantly associated, SEQ%cBR and SEQ%prBR were, and the correlation coefficient was positive. This study suggests that prBR can be typified from spontaneous variabilities along with the more traditional cBR, thus enlarging the possibility of monitoring human cardiovascular control mechanisms.
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08:15-08:30, Paper FrAT11.2 | Add to My Program |
Changes in Heart Rate Variability of Patients with Delirium in Intensive Care Unit |
Oh, Jooyoung | Gwangju Inst. of Science and Tech |
Cho, Dongrae | Gwangju Inst. of Science and Tech |
Kim, Jongin | Gwangju Inst. of Science and Tech |
Heo, Jaeseok | Yonsei Univ |
Park, Jaesub | Yonsei Univ |
Na, Se Hee | Yonsei Univ |
Shin, Cheung Soo | Yonsei Univ |
Kim, Jae-Jin | Yonsei Univ |
Park, Jin Young | Yonsei Univ |
Lee, Boreom | Gwangju Inst. of Science and Tech. (GIST) |
Keywords: Cardiovascular regulation - Heart rate variability, Cardiovascular regulation - Autonomic nervous system, Cardiovascular and respiratory signal processing - Heart Rate and Blood Pressure Variability
Abstract: Delirium is an important syndrome in intensive care unit (ICU) patients, however, its characteristics are still unclear. Many evidences showed that this syndrome can be related to the autonomic instability. In this study, we aimed to investigate the possible alterations of autonomic nervous system (ANS) in delirium patients in ICU. Electrocardiography (ECG) of every ICU patient was measured during routine daily ICU care, and the data were gathered to evaluate the heart rate variability (HRV). HRV of total 60 patients were analyzed in time, frequency and non-linear domains. As a result, we found that heart rates of delirium patients were more variable and irregular than non-delirium patients. These findings may facilitate early detection and prevention of delirium in ICU.
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08:30-08:45, Paper FrAT11.3 | Add to My Program |
A Stochastic and Mathematically Integrative Model of the Control of Human Heart Rate |
BuSha, Brett | The Coll. of New Jersey |
Keywords: Cardiovascular regulation - Heart rate variability
Abstract: The innate variability of the heart rate contains both random and temporally scaled components. The objective of this study was to design a stochastic and mathematically integrative model (SIM) of the control of human heart rate that could replicate the cardiac rhythm during rest and two distinct states of exercise. Heartbeat-to-heartbeat interval (RRI) were recorded from 8 healthy subjects during rest and two exercise levels. Signal memory in RRI sequences was estimated with autocorrelation, and probability density functions (PDFs) were created by fitting polynomial curves to the normalized histograms of the RRI sequences. The SIM generated fictive RRI sequences by randomly selecting RRI values from a PDF and integrating the series using parameters derived from the autocorrelation analysis. Fractal-scaling in the model RRI sequences was quantified with detrended fluctuation analysis. After optimizing the model with the autocorrelation-based and PDF parameters, the SIM was able to produce fictive RRI sequences with significant fractal scaling (statistically assessed with surrogate analysis, p < 0.001), and with fractal-scaling characteristics similar to the original human data (p = 0.62). Increasing the length of the SIM-generated sequences did not alter the temporal scaling of the model sequences. In conclusion, this research demonstrated a stochastic and integrative model that can replicate the temporally correlated characteristics of the human heart rate.
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08:45-09:00, Paper FrAT11.4 | Add to My Program |
Towards the Identification of Subjects Prone to Develop Atrial Fibrillation after Coronary Artery Bypass Graft Surgery Via Univariate and Multivariate Complexity Analysis of Heart Period Variability |
Bari, Vlasta | IRCCS Pol. San Donato |
Ranucci, Marco | Department of Cardiothoracic, Vascular Anesthesia and Intensive |
De Maria, Beatrice | IRCCS Fondazione Salvatore Maugeri, Milano |
Ranuzzi, Giovanni | Department of Cardiothoracic, Vascular Anesthesia and Intensive |
Pistuddi, Valeria | Department of Cardiothoracic, Vascular Anesthesia and Intensive |
Porta, Alberto | Univ. Degli Studi Di Milano |
Keywords: Cardiovascular and respiratory signal processing - Complexity in cardiovascular or respiratory signals, Cardiovascular and respiratory signal processing - Heart Rate and Blood Pressure Variability, Cardiovascular regulation - Autonomic nervous system
Abstract: The assessment of cardiovascular control complexity as derived from spontaneous heart period (HP) fluctuations can be improved by exploiting a multivariate (MV) approach. This work proposes the assessment of a normalized complexity index (NCI) of HP variability according to a k-nearest-neighbor approach based on local predictability performed in a MV nonuniform embedding space. The method allows the selection of the past components of HP, systolic arterial pressure (SAP) and respiration (R) most useful for the prediction of HP fluctuations. The NCI derived from the MV approach (NCI MV) was compared to a NCI computed via the same technique applied in a univariate (UV) embedding space (NCI UV) formed exclusively by HP past samples. Indexes were computed in 130 patients undergoing coronary artery bypass graft (CABG) surgery before and after the induction of general anesthesia. Thirty-eight subjects developed atrial fibrillation (AF) after surgery, while the remaining ones did not (noAF, n=92). Both NCI UV and NCI MV could separate AF from noAF patients and revealed a larger complexity of the AF subjects. However, the statistical power of the NCI MV was superior given that the probability of type I error was smaller than that of NCI UV. The assessment of cardiac control complexity could improve risk stratification of patients at risk of developing AF after CABG surgery.
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09:00-09:15, Paper FrAT11.5 | Add to My Program |
Respiratory-Gated Auricular Vagal Afferent Nerve Stimulation (RAVANS) Effects on Autonomic Outflow in Hypertension |
Sclocco, Roberta | Massachusetts General Hospital, Harvard Medical School |
Garcia, Ronald | Massachusetts General Hospital |
Gabriel, Aileen | Brigham and Women's Hospital |
Kettner, Norman | Logan Coll. of Chiropractic |
Napadow, Vitaly | Massachusetts General Hospital |
Barbieri, Riccardo | Pol. Di Milano |
Keywords: Cardiovascular and respiratory signal processing - Cardiovascular signal processing, Cardiovascular regulation - Heart rate variability, Cardiovascular and respiratory system modeling - Cardiovascular-Respiratory Interactions
Abstract: Transcutaneous stimulation of the auricular branch of the vagus nerve (ABVN) has been proposed as a non-invasive alternative to vagus nerve stimulation (VNS). However, its cardiovagal effects are inconsistent across studies, likely due to inhomogeneity in the stimulation parameters. Here, we evaluate respiratory-gated ABVN stimulation (Respiratory-gated Auricular Vagal Afferent Nerve Stimulation, RAVANS), where the stimuli are delivered in 1 s bursts during the exhalation phase of respiration, thus mimicking the breathing-induced modulation of cardiac vagal activity. In this study, we present preliminary results from an ongoing single-arm, open label trial investigating the effects of different intensities of RAVANS in hypertensive subjects. We found that a mid-intensity RAVANS stimulation (rated as a 5 on a 0-10 scale) increases the cardiovagal tone and reduces the sympathetic tone during a paced breathing task. The present results could contribute to optimize RAVANS as a non-invasive, low-cost therapeutic intervention for hypertension.
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09:15-09:30, Paper FrAT11.6 | Add to My Program |
Multiscale Sample Entropy of Heart Rate and Blood Pressure: Methodological Aspects |
Castiglioni, Paolo | Fondazione Don Carlo Gnocchi ONLUS |
Brambilla, Lorenzo | Fondazione Don Carlo Gnocchi, Parma, Italy |
Bini, Matteo | Department of Clinical and Experimental Medicine, Univ. Of |
Coruzzi, Paolo | Department of Clinical and Experimental Medicine, Univ. Of |
Faini, Andrea | Istituto Auxologico Italiano |
Keywords: Cardiovascular and respiratory signal processing - Heart Rate and Blood Pressure Variability, Cardiovascular and respiratory signal processing - Time-frequency, time-scale analysis of cardiorespiratory variability
Abstract: The entropy of heart rate variability is one of the main features characterizing the complexity of the cardiovascular system. In order to take into account the multiscale nature of cardiovascular regulation, it was proposed to evaluate entropy with a multiscale approach, based on the estimation of Sample Entropy on progressively coarse-grained series (Multiscale Sample Entropy, MSE). Aim of this work is to investigate two methodological aspects related to MSE of cardiovascular signals. The first aspect regards the tolerance below which a couple of points are considered similar in a given embedding dimension, in particular how the way the tolerance is set at each level of coarse graining influences the MSE estimates. The second aspect regards whether heart rate and blood pressure (BP) signals are characterized by different MSE structures. To investigate these aspects, we analyzed 65 continuous BP recordings of more than 90-minute duration in healthy volunteers sitting at rest, and applied MSE estimators to beat-by-beat series of systolic BP, diastolic BP and pulse interval (inverse of heart rate). Results indicate that the way the tolerance is set during coarse graining influences substantially the MSE profile of cardiovascular signals, modifying the relative level of their unpredictability.
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FrAT14 Oral Session, Schaldach Room |
Add to My Program |
Image Classification I |
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Chair: Meng, Max Q.-H. | The Chinese Univ. of Hong Kong |
Co-Chair: Jung, Byungjo | Yonsei Univ |
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08:00-08:15, Paper FrAT14.1 | Add to My Program |
CAD for Prostate Cancer Detection Based on Multiparametric Data |
MERIAUDEAU, fabrice | Univ. De Bourgogne |
LEMAITRE, Guillaume | Le2i - Umr 6306 |
ratsgoo, Mojdeh | Le2i - Umr 6306 |
Martí, Robert | Univ. of Girona |
Keywords: Image classification, Image feature extraction, Magnetic resonance imaging - Other organs
Abstract: Prostate cancer (CaP) is the second most diagnosed cancer in men all over the world. In the last decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have been developed improving diagnosis. In practise, diagnosis can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and computeraided diagnosis systems are being designed to help radiologists in their clinical practice. We propose a new computer-aided system taking advantage of all MRI modalities (i.e., T2-W-MRI, DCE-MRI, DWMRI, MRSI). This system has been extensively tested on a dataset which has been made publicly available.
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08:15-08:30, Paper FrAT14.2 | Add to My Program |
Detecting Imparied Vision Caused by AMD from Gaze Data |
Liu, Huiying | Inst. for Infocomm Res |
Xu, Yanwu | Inst. for Infocomm Res |
Wong, Damon | Inst. for Infocomm Res |
Yow, Ai Ping | Inst. for Infocomm Res |
Laude, Augustinus | Tan Tock Seng Hospital |
Lim, Tock Han | Tan Tock Seng Hospital |
Keywords: Image classification, Infra-red imaging
Abstract: Age Related Macular Degeneration (AMD) is the third leading cause of blindness and the first one in the elderly cite{kawasaki2010prevalence}. AMD usually causes central blindness. In this paper, we propose to detect AMD caused vision impairment from gaze data. Compared with the current methods, e.g., Amsler grid, Microperimetry and Preferential Hyperacuity Perimetry, to detect vision impairments, the proposed method has several advantages. 1) It does not require the patient to stare at a fixed position throughout the test. 2) It does not require the patient to orally or manually report / mark out the vision impairment. 3) It is easy to operate thus a trained nurse is capable of operating the test. We collect gaze data while the patient is performing fixation and smooth pursuit. Features describing the gaze properties are extracted and SVM with linear kernel is trained to detect AMD impaired vision. To implement the proposed method, we collected gaze data of 74 eyes of 57 patients, who are diagnosed as AMD patient by clinicians. Nidek Microperimetry is adopted as gold standard. 57 eyes with normal vision and 17 eyes with impaired vision (blind at more than half test points in Nidek test) are used for test. The result verifies the effectiveness of detecting vision impairment from gaze data.
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08:30-08:45, Paper FrAT14.3 | Add to My Program |
Gabor-Based Automatic Spinal Level Identifi Cation in Ultrasound |
Ikhsan, Mohammad | National Univ. of Singapore |
Tan, Kok Kiong | National Univ. of Singapore |
Oh, Ting Ting | KK Women's and Children's Hospital |
Sng, Ban Leong | KK Women's and Children's Hospital |
Lew, John Paul | KK Women's and Children's Hospital |
Keywords: Image classification, Image feature extraction, Ultrasound imaging - Other organs
Abstract: This paper presents an automatic lumbar spine level identification system based on image processing of ultrasound images. The goal is to aid anesthetists in identifying the correct spinal level during epidural anesthesia. Spine level identification is initiated by detecting the location of the sacrum using a classifier based on a support vector machine. Image stitching is then conducted to produce a panorama image of the spinal area. During this process, the location of spinal processes are enhanced using a Gabor filter and detected through template matching. The locations of the spinal processes are tracked and used as an overlay on the ultrasound image in real-time. The system then informs the anesthetists when the correct spinal level has been reached. The system was evaluated on forty volunteers by two anesthetists with varying experience level and was able to detect the correct position of the L3-L4 spinal level in all of the volunteers. The average time taken to produce the location of the L3-L4 spinal level was 30.92 seconds. The results show that the system can quickly and accurately detect the location of the target spinal level.
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08:45-09:00, Paper FrAT14.4 | Add to My Program |
Image Recognition with Missing-Features Based on Gaussian Mixture Model and Graph Constrained Nonnegative Matrix Factorization |
Zhang, Zhuyan | East China Univ. of Science and Tech |
Zhu, Hongqing | East China Univ. of Science and Tech |
Tao, Xuan | East China Univ. of Science and Tech |
Keywords: Image classification
Abstract: The demand for automatically recognizing medical images for screening, reference and management is growing faster than ever. Missing data phenomenon in medical image applications is common existence, and it could be inevitable. In this paper, we have addressed the problem of recognizing medical images with missing-features via Gaussian mixture model (GMM)-based approach. Since training a GMM by directly using high-dimensional feature vectors will result in instability, we have proposed a novel strategy to train the GMM from the corresponding reduced-dimensional one. The proposed method contains training and test phases. The former contains feature extraction, graph constrained nonnegative matrix factorization (NMF), GMM training, and the alternating expectation conditional maximization (AECM) for extending the reduced-dimensional GMM. In test phase, two methods, marginalizing GMM using Bayesian decision (MGBD) and conditional mean imputation (CMI), are applied to impute missing-features. Posterior probability of test images is calculated to identify objects. Experimental results on three real datasets demonstrate the feasibility and efficiency of the proposed scheme.
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09:00-09:15, Paper FrAT14.5 | Add to My Program |
Gastrointestinal Bleeding Detection in Wireless Capsule Endoscopy Images Using Handcrafted and CNN Features |
Jia, Xiao | The Chinese Univ. of Hong Kong |
Meng, Max Q.-H. | The Chinese Univ. of Hong Kong |
Keywords: Image classification, Image feature extraction
Abstract: Gastrointestinal (GI) bleeding detection plays an essential role in wireless capsule endoscopy (WCE) examination. In this paper, we present a new approach for WCE bleeding detection that combines handcrafted (HC) features and convolutional neural network (CNN) features. Compared with our previous work, a smaller-scale CNN architecture is constructed to lower the computational cost. In experiments, we show that the proposed strategy is highly capable when training data is limited, and yields comparable or better results than the latest methods.
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09:15-09:30, Paper FrAT14.6 | Add to My Program |
Automated Angiodysplasia Detection from Wireless Capsule Endoscopy |
Noya, Ferran | Automatic Control Department, Univ. Pol. De Catalun |
Álvarez-González, Marco Antonio | Endoscopy Unit, Department of Digestive Diseases, Hospital Del M |
Benitez, Raul | Univ. Pol. De Catalunya |
Keywords: Image classification, Image feature extraction, Image segmentation
Abstract: We present a novel system for the automatic detection of angiodysplasia lesions from capsule endoscopy images. The approach identifies potential regions of interest and classifies them using a combination of color-based, texture, statistical and morphological features. A boosted decision tree classification method is used in order to overcome the problem of unbalanced sampling between pathological and non-pathological regions. The lesion detection method has been designed and validated using a lesion database labelled by an expert. The approach achieves a sensitivity of 89.51% and a specificity of 96.8%, thus providing a high performance in the detection of angiodysplasia lesions.
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FrAT15 Special Session, Webster Room |
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Big Data to Improve Outcomes, Process, and Services in Health |
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Chair: Akay, Metin | Univ. of Houston |
Co-Chair: Fico, Giuseppe | Tech. Univ. of Madrid |
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, Paper FrAT15. | Add to My Program |
Big Data to Improve Outcomes, Process, and Services in Health |
Akay, Metin | Univ. of Houston |
Fico, Giuseppe | Univ. Pol. de Madrid |
Guillen, Sergio | TSB-MYSPHERA S.L. |
Arredondo, María Teresa | Tech. Univ. of Madrid |
Sakellarios, Antonis | Unit of Medical Tech. and Application Systems, Dept of Material Science, Univ. of Ioannina |
Scilingo, Enzo Pasquale | Univ. of Pisa |
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FrAT17 Oral Session, Einthoven Hall |
Add to My Program |
Signal Processing - Cardiovascular Signals |
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Chair: Burattini, Laura | Univ. Pol. Delle Marche |
Co-Chair: Scilingo, Enzo Pasquale | Univ. of Pisa |
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08:00-08:15, Paper FrAT17.1 | Add to My Program |
Intracardiac Electrogram Envelope Detection During Atrial Fibrillation Using Fast Orthogonal Search |
Hashemi, Javad | Queen's Univ |
Shariat, Mohammad Hassan | Queen’s Univ. Kingston, Ontario, Canada |
Redfearn, Damian P | Queen's Univ |
Keywords: Physiological systems modeling - Signal processing in physiological systems, Nonlinear dynamic analysis - Volterra-Wiener models in physiological systems, Time-frequency and time-scale analysis - Wavelets
Abstract: The performance of any intra-cardiac electrogram processing method is limited by the accuracy of its activation detection approach. The most common activation detection approaches in the literature aim to find the highest peak in the activation envelope disregarding the start and end points. However, the duration of the activation can be used to extract useful information such as wave collisions. In this work, we propose a novel orthogonal-based (FOS) approach for fast and accurate estimation of the start and end of the activations (activation envelope) in intracardiac recordings during atrial fibrillation. Wavelet decomposition of the signals was used to create a pool of basis functions for the proposed modeling method. The database included 24 recordings of approximate length of 6s obtained from inner walls of atria of 5 patients who underwent catheter ablation therapy. The start and end of activations in each electrogram was manually annotated by an expert electrophysiologist and the annotations were used as golden standard to calculate the performance of our envelope detection method. The results show promising performance and excellent robustness to training data for our proposed method with respect to envelope estimation error.
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08:15-08:30, Paper FrAT17.2 | Add to My Program |
Statistical Baseline Assessment in Cardiotocography |
Agostinelli, Angela | Pol. Univ. of Marche |
Braccili, Eleonora | Univ. Pol. Delle Marche |
Marchegiani, Enrico | Univ. Pol. Delle Marche |
Rosati, Riccardo | Univ. Pol. Delle Marche |
Sbrollini, Agnese | Univ. Pol. Delle Marche |
Burattini, Luca | Univ. Pol. Delle Marche |
Morettini, Micaela | Univ. Pol. Delle Marche |
Di Nardo, Francesco | Pol. Univ. of Marche |
Fioretti, Sandro | Univ. Pol. Delle Marche |
Burattini, Laura | Univ. Pol. Delle Marche |
Keywords: Physiological systems modeling - Signal processing in physiological systems, Physiological systems modeling - Signals and systems
Abstract: Cardiotocography (CTG) is the most common non-invasive diagnostic technique to evaluate fetal well-being. It consists in the recording of fetal heart rate (FHR; bpm) and maternal uterine contractions. Among the main parameters characterizing FHR, baseline (BL) is fundamental to determine fetal hypoxia and distress. In computerized applications, BL is typically computed as mean FHR±ΔFHR, with ΔFHR=8 bpm or ΔFHR=10 bpm, both values being experimentally fixed. In this context, the present work aims: to propose a statistical procedure for ΔFHR assessment; to quantitatively determine ΔFHR value by applying such procedure to clinical data; and to compare the statistically-determined ΔFHR value against the experimentally-determined ΔFHR values. To these aims, the 552 recordings of the “CTU-UHB intrapartum CTG database” from Physionet were submitted to an automatic procedure, which consisted in a FHR preprocessing phase and a statistical BL assessment. During preprocessing, FHR time series were divided into 20-min sliding windows, in which missing data were removed by linear interpolation. Only windows with a correction rate lower than 10% were further processed for BL assessment, according to which ΔFHR was computed as FHR standard deviation. Total number of accepted windows was 1192 (38.5%) over 383 recordings (69.4%) with at least an accepted window. Statistically-determined ΔFHR value was 9.7 bpm. Such value was statistically different from 8 bpm (P<10-19) but not from 10 bpm (P=0.16). Thus, ΔFHR=10 bpm is preferable over 8 bpm because both experimentally and statistically validated.
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08:30-08:45, Paper FrAT17.3 | Add to My Program |
Nonlinear Analysis of Heart Rate Variability for the Assessment of Dysphoria |
Greco, Alberto | Univ. of Pisa |
Messerotti Benvenuti, Simone | Univ. of Padova |
Gentili, Claudio | Univ. of Pisa |
Palomba, Daniela | Univ. of Padova |
Valenza, Gaetano | Univ. of Pisa |
Scilingo, Enzo Pasquale | Univ. of Pisa |
Keywords: Signal pattern classification, Nonlinear dynamic analysis - Biomedical signals, Physiological systems modeling - Signal processing in physiological systems
Abstract: Dysphoric patients show symptoms associated with Major Depression, although within a narrowed symptomatology spectrum. In prevailing practice, clinicians assess Dysphoria through psychological scores and questionnaires exclusively, therefore without taking into account objective biomarkers. In this study, we investigated heartbeat linear and nonlinear dynamics aiming to an objective assessment of Dysphoria. To this end, we derived standard and nonlinear measures from heart rate variability (HRV) series gathered from dysphoric (n=14) and nondysphoric (n=17) undergraduate students during 5 minutes of resting state. We performed both statistical and pattern recognition analyses in order to discern the two groups. Results showed significant group-wise differences in HRV nonlinear metrics exclusively, suggesting a crucial role of nonlinear sympatho-vagal dynamics in Dysphoria. Furthermore, we achieved a classification accuracy of 77.52% for the automatic identification of Dysphoria at a single subject level.
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08:45-09:00, Paper FrAT17.4 | Add to My Program |
Classification Enhancement for Post-Stroke Dementia Using Fuzzy Neighborhood Preserving Analysis with QR-Decomposition |
Al-Qazzaz, Noor | UKM |
Md Ali, Sawal Hamid | National Univ. of Malaysia |
Siti Anom, Ahmad | Univ. Putra Malaysia |
Escudero, Javier | Univ. of Edinburgh |
Keywords: Nonlinear dynamic analysis - Biomedical signals, Time-frequency and time-scale analysis - Wavelets, Signal pattern classification
Abstract: The aim of this study was to discriminate the electroencephalogram (EEG) background activity of 5 vascular dementia (VaD) patients, 15 stroke-related patients with mild cognitive impairment (MCI), and 15 control healthy subjects during a working memory (WM) task. We used independent component analysis (ICA) and wavelet transform (WT) as a hybrid pre-processing approach for EEG artifact removal. Three different features were extracted from the cleaned EEG signals: spectral entropy (SpecEn), permutation entropy (PerEn) and Tsallis entropy (TsEn). Two classification schemes were applied – support vector machine (SVM) and k-nearest neighbors (kNN) – with fuzzy neighborhood preserving analysis with QR-decomposition (FNPAQR) as a dimensionality reduction technique. The FNPAQR dimensionality reduction technique increased the SVM classification accuracy from 82.22% to 90.37% and from 82.6% to 86.67% for kNN. These results suggest that FNPAQR consistently improves the discrimination of VaD, stroke-related MCI patients and control healthy subjects and it could be a useful feature selection to help the identification of patients with VaD and stroke-related MCI.
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09:00-09:15, Paper FrAT17.5 | Add to My Program |
Attenuation of Vagal Modulation with Aging: Univariate and Bivariate Analysis of HRV |
Costa Oliveira Junior, Evandro | Univ. of Brasilia |
Oliveira, Flavia M. G. S. A. | Univ. of Brasilia |
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FrAT18 Oral Session, Montgomery Hall |
Add to My Program |
Nonlinear Dynamic Analysis I - Biomedical Signals |
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Co-Chair: Sajib, Saurav Z K | Kyung Hee Univ |
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08:00-08:15, Paper FrAT18.1 | Add to My Program |
Multiscale Dispersion Entropy for the Regional Analysis of Resting-State Magnetoencephalogram Complexity in Alzheimer’s Disease |
Azami, Hamed | Univ. of Edinburgh |
Kinney-Lang, Eli | Univ. of Edinburgh |
Ebied, Ahmed | Univ. of Edinburgh |
Fernandez, Alberto | Univ. Complutense De Madrid |
Escudero, Javier | Univ. of Edinburgh |
Keywords: Nonlinear dynamic analysis - Biomedical signals
Abstract: Alzheimer’s disease (AD) is a progressive and irreversible brain disorder affecting memory, thinking, and emotion. It is a prominent cause of dementia and a major societal problem worldwide. The complexity of brain recordings has been successfully used to help to characterize AD. We have recently introduced multiscale dispersion entropy (MDE) as a very fast and powerful tool to quantify the complexity of signals across several time scales. We now seek to assess the ability of MDE, in comparison with multiscale permutation entropy (MPE) and multiscale entropy (MSE), to discriminate resting-state magnetoencephalogram (MEG) recordings of 36 AD patients from 26 elderly age-matched control subjects. The results confirmed that MDE, unlike MSE, does not lead to undefined values, especially at high temporal scales. Moreover, the significant differences for AD patients versus controls obtained by MDE, in comparison with MSE and MPE, were at a larger number of scales. In addition, the computation time for our recently developed MDE was considerably less than that for the MSE and even the MPE.
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08:15-08:30, Paper FrAT18.2 | Add to My Program |
Gait Variability Assessment in Neuro-Degenerative Patients by Measuring Complexity of Independent Sources |
Heydarzadeh, Mehrdad | The Univ. of Texas at Dallas |
Nourani, Mehrdad | Univ. of Texas at Dallas |
Tan, Chin-Tuan | Univ. of Texas, Dallas |
Ostadabbas, Sarah | Northeastern Univ |
Keywords: Signal pattern classification, Independent component analysis, Physiological systems modeling - Signal processing in physiological systems
Abstract: Patients suffering from neuro-degenerative diseases have difficulties with normal locomotion. This problem progresses with the course of disease. Gait assessment is an effective way of diagnosing the disease and quantifying its progress which can effectively prevent falls. In this paper, an automatic assessment method for analyzing gait data obtained by force sensor insoles is introduced. The gait analysis method is based on measuring the complexity of gait data after extracting independent sources. The results are promising an average accuracy of 94% for three different diseases.
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08:30-08:45, Paper FrAT18.3 | Add to My Program |
Complexity Analysis of Resting State Fmri Signals in Depressive Patients |
Ho, Pei-Shan | National Tsing Hua Univ. Hsinchu |
Lin, Chemin | Keelung Chang Gung Memorial Hospital |
Chen, Guan-Yen | National Tsing Hua Univ |
Liu, Ho-Ling | Univ. of Texas, MD Anderson Cancer Center |
Huang, Chih-Mao | National Chiao Tung Univ |
Lee, Tatia Mei-Chun | The Univ. of Hong Kong |
Lee, Shwu-Hua | Linkou Chang Gung Memorial Hospital |
Wu, Shun Chi | National Tsing Hua Univ |
Keywords: Nonlinear dynamic analysis - Biomedical signals, Coupling and synchronization - Coherence in biomedical signal processing
Abstract: Analysis of brain signal complexity reveals the intrinsic network dynamics and is widely utilized in the investigation of mechanisms in mental disorders. In this study, the complexity of resting-state functional magnetic resonance imaging (fMRI) signals was explored in patients with depression using multiscale entropy (MSE). Thirty-five patients diagnosed with depression and 22 age- and gender-matched healthy controls were considered. The MSE profiles in 5 brain networks of the 2 participant groups were evaluated and analyzed. The results showed that depressive patients exhibited higher complexity in the left frontoparietal network than that seen in healthy controls, which is known to be critical for executive control functions. Through this study, the efficacy of MSE in identifying and understanding the mental disorders was also demonstrated.
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08:45-09:00, Paper FrAT18.4 | Add to My Program |
Predicting Learning Dynamics in Multiple-Choice Decision-Making Tasks Using a Variational Bayes Technique |
Yousefi, Ali | Massachusetts General Hospital and Harvard Medical School |
Kakooee, Reza | Tarbiat Modares Univ |
Hamidi Beheshti, Mohammad Taghi | Tarbiat Modares Univ |
Dougherty, Darin | Massachusetts General Hospital |
Eskandar, Emad | Massachusetts General Hospital |
Widge, Alik | Massachusetts General Hospital |
Eden, Uri | Boston Univ |
Keywords: Nonlinear dynamic analysis - Nonlinear filtering, Nonlinear dynamic analysis - Biomedical signals
Abstract: Multiple-Choice Decision-Making Tasks are widely used to analyze behavior and infer underlying cognitive states that shape the decision and learning processes. The behavioral signals recorded in these tasks are dynamic and often non-Gaussian – for instance, when learning a multiple choice association task. Previously developed estimation algorithms for latent behavioral variables do not address multiple-choice responses. In this research, we use a state-space modeling framework to predict a cognitive learning state related to multiple choice decisions, which are best described by a multinomial distribution. The proposed algorithm combines a multinomial filter/smoother and a variational Bayes technique to estimate the dynamics of a learning state vector. The algorithm is applied to decision response data recorded from non-human primates (NHPs) performing a Multiple-Choice Decision Task.
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09:00-09:15, Paper FrAT18.5 | Add to My Program |
A Closed-Form Unsupervised Geometry-Aware Dimensionality Reduction Method in the Riemannian Manifold of SPD Matrices |
Congedo, Marco | CNRS, Univ. Grenoble Alpes, Grenoble Inst. of Tech |
Rodrigues, Pedro Luiz Coelho | Escola Pol. USP |
Bouchard, Florent | Gipsa-Lab, Univ. Grenoble Alpes |
Barachant, Alexandre | Independent Res |
Jutten, Christian | Univ. of Grenoble |
Keywords: Nonlinear dynamic analysis - Nonlinear filtering, Principal component analysis
Abstract: Riemannian geometry has been found accurate and robust for classifying multidimensional data, for instance in brain-computer interfaces based on electroencephalography. Given a number of data points on the manifold of symmetric positive-definite matrices, it is often of interest to embed these points in a manifold of smaller dimension. This is necessary for large dimensions in order to preserve accuracy and useful in general to speed up computations. Geometry-aware methods try to accomplish this task while respecting as much as possible the geometry of the original data points. We provide a completely unsupervised closed-form solution for this problem and we show that it allows substantial dimensionality reduction without affecting the classification accuracy in two large public brain-computer interface data bases.
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09:15-09:30, Paper FrAT18.6 | Add to My Program |
Real-Time Physiological Tremor Estimation Using Recursive Singular Spectrum Analysis |
Adhikari, Kabita | Newcastle Univ |
Tatinati, Sivanagaraja | Nanyang Tech. Univ |
Veluvolu, Kalyana C. | Kyungpook National Univ |
Chambers, Jonathon A. | Newcastle Univ |
Nazarpour, Kianoush | Newcastle Univ |
Keywords: Nonlinear dynamic analysis - Biomedical signals, Physiological systems modeling - Signal processing in physiological systems, Principal component analysis
Abstract: Physiological hand tremor causes undesirable vibration of hand-held surgical instruments which results in imprecisions and poor surgical outcomes. Existing tremor cancellation algorithms are based on detection of the tremulous motion from the whole motion; then adding an anti-phase tremor signal to the whole motion to it cancel out. These techniques are based on adaptive filtering algorithms which need a reference signal that is correlated with the actual tremor signal. Hence, adaptive algorithms use a non-linear phase filter to pre-filter the tremor signal either offline or in real-time. However, pre-filtering causes unnecessary delays and non-linear phase distortions as the filter has frequency selective delays. Consequently, the anti-phase tremor signal cannot be generated accurately which results in poor tremor cancellation. In this paper, we present a new technique based on singular spectrum analysis (SSA) and its recursive version, that is, recursive singular spectrum analysis (RSSA). These algorithms decompose the whole motion into dominant voluntary components corresponding to larger eigenvalues and oscillatory tremor components having smaller eigenvalues. By carefully selecting a group of specific decomposed signals based on their eigenvalues and spectral range, both voluntary and tremor signals can be reconstructed accurately. We tested the SSA and RSSA algorithms with real physiological tremor data that was recorded from five novice subjects. This new approach shows the tremor signal can be estimated from the whole motion with an accuracy of up to 85% offline. In real-time, tolerating a delay of ≈72ms, tremor signal can be estimated with at least 70% accuracy. This delay was found to be one-tenth of the delay caused by a conventional linear phase filter to achieve similar performance in real-time.
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FrBT1 Oral Session, Roentgen Hall |
Add to My Program |
Signal Pattern Classification - EEG I |
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Chair: Bezerianos, Anastasios | National Univ. of Singapore |
Co-Chair: Zhang, Dan | Tsinghua Univ |
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10:50-11:05, Paper FrBT1.1 | Add to My Program |
Integrating Channel Selection and Feature Selection in a Real Time Epileptic Seizure Detection System |
Wang, Hongda | The Chinese Univ. of Hong Kong |
Shi, Weiwei | Shenzhen Univ |
choy, chiu sing | The Chinese Univ. of Hong Kong |
Keywords: Signal pattern classification, Data mining and processing in biosignals, Time-frequency and time-scale analysis - Time-frequency analysis
Abstract: Automated real time seizure detection is a challenging work since the sensitivity, false detection rate and seizure onset detection latency need to be considered simultaneously. Traditional pattern recognition and classification system with fixed channels and features usually suffers huge performance variation due to patient specificity and algorithm adaptability. To address this problem, we propose a two stage seizure detection system which has integrated channel selection and feature selection as an off-line preprocessing prior to final model is constructed. This system enables patient specific channel adjustment and flexible feature set extraction for each patient, thus a more compact and reliable model could be developed for patient customization. Employing the two stage scheme to the raw EEG data not only decreases the hardware cost in signal readout and feature extraction, but also remarkably improve the detection sensitivity and reduce false detections. Mutual information based method has been used for channel selection, while Random Forests and nonlinear SVM-RFE have been evaluated for feature selection. The whole system has achieved a mean detection latency of 6 seconds and false detection rate of 0.356 per hour. With two missed detections on the test database, the sensitivity is 74.2% by sample or 98.4% by record. Our design is also hardwarefriendly, which could be finally implemented in an on-chip closed loop neural modulation system.
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11:05-11:20, Paper FrBT1.2 | Add to My Program |
Evidences of Brain Functional Deficits Following Sport-Related Mild Traumatic Brain Injury |
Munia, Tamanna Tabassum Khan | Univ. of North Dakota |
Haider, Md. Ali | Univ. North Dakota |
Fazel-Rezai, Reza | Univ. of North Dakota |
Keywords: Physiological systems modeling - Signal processing in physiological systems, Signal pattern classification
Abstract: Sport related mild traumatic brain injury (mTBI), generally known as a concussion, is a worldwide critical public health concern nowadays. Despite growing concern emphasized by scientific research and recent media presentation regarding mTBI and its effect in athletics life, the management, and prevention of mTBI are still not properly done. The evaluation mainly hampered due to the lack of proper knowledge, subjective nature of assessment tools including the fact that the brain functional deficits after mTBI can be mild or hidden. As a result, development of an effective tool for proper management of these mild incidents is a subject of active research. In this paper, to examine the neural substrates following mTBI, an analysis based on electroencephalogram (EEG) from twenty control and twenty concussed athletes is presented. Preliminary results suggest that the concussed athletes have a significant increase in delta, theta and alpha power but a decrease in beta power. We also calculated the power for individual frequencies from 1 Hz to 40 Hz in order to find out the specific frequencies with the highest deficits. The significant deficiencies were found at 1-2 Hz of delta band, 6-7 Hz of theta band, 8-10 Hz of the alpha band, and 16-18 Hz and 24-29 Hz of the beta band. Though there was no significant difference as observed in gamma band, we found the deficit was significant at 34-36 Hz range within the gamma band. The observed deficits at various frequencies demonstrate that even if there is no significant difference in the traditional frequency bands, there may be hidden deficits at some specific frequencies within a frequency band. These preliminary results suggest that the EEG analysis at each unity frequency may be more promising means of identifying the neuronal damage than the traditional frequency band based analysis. Eventually, the proposed analysis can provide an improved approximation to monitor the pathophysiological recovery after a concussion.
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11:20-11:35, Paper FrBT1.3 | Add to My Program |
Estimating Unmeasured Invasive EEG Signals Using a Reduced-Order Observer |
Gunnarsdottir, Kristin | Johns Hopkins Univ |
Li, Adam | Neuromedical Control Systems Lab |
Bulacio, Juan | Cleveland Clinic |
Gonzalez-Martinez, Jorge | Cleveland Clinic |
Sarma, Sridevi V. | Johns Hopkins Univ |
Keywords: Physiological systems modeling - Multivariate signal processing, Physiological systems modeling - Signal processing in physiological systems, Time-frequency and time-scale analysis - Nonstationary processing
Abstract: Epilepsy affects around 50 million people worldwide. Over 30% of patients are drug-resistant where the only treatment may be surgical resection of the epileptogenic zone (EZ), the region of the brain that generates seizures. Identification of the EZ is often based on invasive EEG recordings. As such, surgical outcome relies heavily on precise and dense placement of EEG electrodes into the brain. Despite large brain regions being removed, success rates barely reach 65%. This gives rise to the “missing electrode problem”, where clinicians want to know what neural activity looks like between sparsely implanted electrodes. Solving this problem will enable more accurate localization of the EZ. In this paper, we demonstrate the first steps towards developing a computational platform to estimate neural activity at the “missing electrodes” using a reduced-order observer from control theory. Specifically, we constructed a sequence of discrete time Linear Time-Invariant (LTI) models using the available EEG data from two epilepsy patients. Then, we used the models to simulate EEG data and remove selected signals (“missing” states) from the simulated data set. Finally, we used a reduced-order observer to estimate the signals of these “missing” states and evaluated performance by comparing the observer estimates to the simulated EEG time series.
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11:35-11:50, Paper FrBT1.4 | Add to My Program |
A Mental Fatigue Index Based on Regression Using Mulitband EEG Features with Application in Simulated Driving |
Dimitrakopoulos, Georgios | Univ. of Patras |
Kakkos, Ioannis | National Univ. Singapore |
Thakor, Nitish | Johns Hopkins Univ |
Bezerianos, Anastasios | National Univ. of Singapore |
Sun, Yu | National Univ. of Singapore |
Keywords: Physiological systems modeling - Signal processing in physiological systems
Abstract: Development of accurate fatigue level prediction models is of great importance for driving safety. In parallel, a limited number of sensors is a prerequisite for development of applicable wearable devices. Several EEG-based studies so far have performed classification in two or few levels, while others have proposed indices based on power ratios. Here, we utilized a regression Random Forest model in order to provide more accurate continuous fatigue level prediction. In detail, multiband power features were extracted from EEG data recorded from one hour simulated driving task. Next, cross-subject regression was performed to obtain common fatigue-related discriminative features. We achieved satisfactory prediction accuracy and simultaneously we minimized required electrodes, proposing to use a set of 3 electrodes.
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11:50-12:05, Paper FrBT1.5 | Add to My Program |
Decoding Brain Cognitive Activity across Subjects Using Multimodal M/eeg Neuroimaging |
Fatima, Sarwat | National Univ. of Science and Tech |
Kamboh, Awais Mehmood | School of Electrical Engineering and Computer Science, National |
Keywords: Signal pattern classification, Data mining and processing - Pattern recognition, Physiological systems modeling - Multivariate signal processing
Abstract: Brain decoding is essential in understanding of where and how information is encoded inside the brain. Existing literature has shown that a good classification accuracy is achievable in decoding for single subjects, but multi-subject classification has proven difficult due to the inter-subject variability.In this paper, multi-modal neuroimaging was used to improve two-class multi-subject classification accuracy in a cognitive task. In this transfer learning problem, a feature space based on special-form covariance matrices manipulated with riemannian geometry are used. A supervised two-layer hierarchical model was trained iteratively for estimating classification accuracies. Results are reported on a publically available multi-subject, multi-modal human neuroimaging dataset from MRC Cognition and Brain Sciences Unit, University of Cambridge. The dataset contains simultaneous recordings of electroencephalography (EEG) and magnetoencephalography (MEG). Our model attained, using leave-one-subject-out cross-validation, classification accuracy of 70.82% for single modal EEG, 81.55% for single modal MEG and 84.98% for multi-modal M/EEG.
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12:05-12:20, Paper FrBT1.6 | Add to My Program |
EEG-Based Approach-Withdrawal Index for the Pleasantness Evaluation During Taste Experience in Realistic Settings |
Di Flumeri, Gianluca | Univ. of Rome Sapienza |
Arico, Pietro | Fondazione Santa Lucia |
Borghini, Gianluca | Univ. of Rome Sapienza |
Sciaraffa, Nicolina | Department of Computer, Control and Management Engineering, Univ |
Maglione, Anton Giulio | Univ. of Rome Sapienza |
Rossi, Dario | Univ. of Rome Sapienza |
Modica, Enrica | Univ. of Rome Sapienza |
Mascarell Llorens, Ignacio | Dept. of Clinical and Experimental Neuroscience, Univ. of M |
Trettel, Arianna | BrainSigns |
Babiloni, Fabio | Univ. of Rome |
Colosimo, Alfredo | Univ. of Rome "Sapienza" |
Herrero Exquerro, Maria Trinidad | Univ. of Murcia |
Keywords: Physiological systems modeling - Signal processing in physiological systems, Time-frequency and time-scale analysis - Time-frequency analysis, Physiological systems modeling - Signals and systems
Abstract: The taste is a vital sense in humans, because of its active role in regulating nutrition or avoiding harmful substances. Several studies showed the important role of the brain Pre-Frontal Cortex in decoding information coming from the gustatory system. It is also widely known, in neuroscientific literature, that the asymmetry of Pre-Frontal Cortex Activity is closely linked to the feeling of pleasantness experienced by the subject during sensorial stimulation. In this regard, from the electroencephalographic (EEG) signal it is possible to estimate the Approach/Withdrawal (AW) index, which has been largely investigated and validated in scientific literature, regarding visual, acoustic and olfactory stimuli. On the contrary there are no evidences about the relationship between such an index and taste. In this work, it has been investigated if such AW index could provide reliable information regarding the pleasantness felt during taste experience. In particular, the EEG-based AW indexes of 15 healthy subjects tasting 7 creams of different flavor have been compared with the subjective appreciation judgement. The results showed a high significant correlation between EEG-based and subjective data. Also, it has been used to statistically investigate differences of perception between the different flavors, demonstrating the potential applicability of such technology towards real applications.
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12:05-12:20, Paper FrBT1.7 | Add to My Program |
ICA on Sensor or Source Data: A Comparison Study in Deriving Resting State Networks from EEG |
Li, Chuang | Univ. of Oklahoma |
Yuan, Han | Univ. of Oklahoma |
Urbano, Diamond | Laureate Inst. for Brain Res |
Cha, Yoon-Hee | Laureate Inst. of Brain Res |
Ding, Lei | Univ. of Oklahoma |
Keywords: EEG imaging
Abstract: Resting state networks (RSNs) are human brain networks formed by spontaneous activity fluctuations in distributed brain regions when people are in task-free and awake state. RSNs have been so far extensively studied using functional magnetic resonance imaging (fMRI). Recently, electroencephalography (EEG) and magnetoencephalography (MEG) have also been used to derive RSNs, in which independent component analysis (ICA) is the key step. In these studies, ICA has been either directly applied to recorded data at sensors (sensor-space ICA) or estimated source data from sensors using inverse source imaging techniques (source-space ICA). Both sensor-space and source-space ICAs have demonstrated the capability in finding RSNs from EEG/MEG data and their results showed strong correlations to fMRI RSNs. However, their performance was hardly compared even differences have been observed in their results. In the present study, we compared the source-space and sensor-space ICAs in reconstructing spatial, temporal and spectral features of RSNs in both simulated and real EEG data. Results from simulated data indicated that the source-space ICA has better performance in reconstructing spatial, temporal, and spectral feature of RSNs. Results from resting-sate EEG data in seven healthy participants also showed the difference between two procedures and, through the comparison with RSN templates constructed from fMRI data, the source-space ICA indicated relatively better performance than the sensor-space ICA.
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FrBT2 Oral Session, Cho Room |
Add to My Program |
Innovative Ultrasound Imaging |
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Chair: Lavarello, Roberto | Pontificia Univ. Catolica Del Peru |
Co-Chair: Park, Kwan Kyu | Hanyang Univ |
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10:50-11:05, Paper FrBT2.1 | Add to My Program |
Multimodal Ultrasound Imaging Based Diagnosis of Liver Cancers with a Two-Stage Multi-View Learning Framework |
Yiyi, Qian | Shanghai Univ |
Shi, Jun | Shanghai Univ |
Zheng, Xiao | Shanghai Univ |
Zhang, Qi | Shanghai Univ |
Lehang, Guo | Shanghai Tenth People’s Hospital |
Dan, Wang | Shanghai Tenth People’s Hospital |
Huixiong, Xu | Shanghai Tenth People’s Hospital |
Keywords: Image classification, Ultrasound imaging - Other organs
Abstract: Computer-aided diagnosis (CAD) of liver cancers on contrast-enhanced ultrasound (CEUS) has attracted considerable attention in recent years. The enhancement patterns on CEUS for liver lesions consist of the arterial, portal venous and late phases. Several typical images selected from these three phases can provide reliable information basis for diagnosis of liver lesions. Therefore, we propose to develop a CAD framework for liver cancers with only one B-mode images and three typical CEUS images selected from three enhancement patterns, which simulates the clinical diagnosis mode of radiologists. Moreover, a framework of two-stage multi-view learning (TS-MVL) is proposed to perform both feature-level and classifier-level MVL for the diagnosis of liver cancers with multimodal ultrasound images. We propose to apply the nonlinear kernel matrix (NKM) algorithm to effectively fuse the features of multimodal ultrasound images, and then perform the multiple kernel boosting (MKB) algorithm to promote the predictive performance of multiple classifiers according to multi-view features. The experimental results indicate that the proposed algorithm outperforms the commonly used multi-view learning algorithms.
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11:05-11:20, Paper FrBT2.2 | Add to My Program |
Myocardial Elastogram Using a Fast Mapping Algorithm |
Wang, Yinong | Inst. of Medical Information, School of Biomedical Engineeri |
Song, Xiangfen | Inst. of Medical Information, School of Biomedical Engineeri |
Huang, Zhijie | Inst. of Medical Information, School of Biomedical Engineeri |
Wang, Qing | Southern Medical Univ |
Keywords: Ultrasound imaging - Cardiac, Ultrasound imaging - Elastography, Cardiac imaging and image analysis
Abstract: Ultrasound myocardial elastography is a promising technique to estimate regional myocardial function. In this study, we proposed a fast mapping method to map myocardial elastogram. A nude mouse’s heart was scanned in supine position by an ultrasound system. The parasternal long-axis view of the heart and the ultrasound radio frequency (RF) signals were acquired for dynamic estimation of myocardial elasticity. The displacement and strain were calculated using analytic minimization (AM) and linear polynomial curve fitting method, respectively. The fast mapping method was proposed to map myocardial elastogram. The results display the contraction of myocardium intuitively. The method in this study is proved to have a potential to estimate viable myocardium in the future.
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11:20-11:35, Paper FrBT2.3 | Add to My Program |
Image-Guided Laparoscopic Pelvic Lymph Node Dissection Using Stereo Visual Tracking Free-Hand Laparoscopic Ultrasound |
Ma, Lei | School of Bioengineering, the Univ. of Tokyo |
Nakamae, Kenta | The Univ. of Tokyo |
Wang, Junchen | The Univ. of Tokyo |
Kiyomatsu, Hidemichi | The Univ. of Tokyo |
Tsukihara, Hiroyuki | The Univ. of Tokyo |
Kobayashi, Etsuko | The Univ. of Tokyo |
Sakuma, Ichiro | The Univ. of Tokyo |
Keywords: Ultrasound imaging - Interventional, Image segmentation, Rigid-body image registration
Abstract: Laparoscopic pelvic lymph node dissection is a delicate operation because the pelvic arteries, which should be located firstly to guide the dissection, are often concealed by tissues and missed in the endoscopic view, so artery can be hurt when located inaccurately. In order to improve the safety and efficiency of the dissection, we developed an image-guided navigation system to provide the position information of the pelvic arteries for surgeons by registering the 3D artery model extracted from CT images to 3D model reconstructed from free-hand laparoscopic ultrasound images. The ultrasound probe is tracked using a proposed stereo vision based tracking strategy, which can simplify the system and reduce the setting time, and the artery is segmented from 2D ultrasound images using a local phase based snakes framework. The accuracy of navigation system using the stereo visual tracking was estimated using a phantom, and the TRE error was 1.58±0.70mm, and the feasibility of the proposed navigation system was confirmed in animal experiment.
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11:35-11:50, Paper FrBT2.4 | Add to My Program |
Tracking Large Anterior Mitral Leaflet Displacements by Incorporating Optical Flow in an Active Contours Framework |
Sultan, Malik Saad | Univ. of Porto |
Martins, Nelson | Enermeter, Sistemas De Medição, Lda & Inst. De Telecomunicac |
Eva, Costa | Enermeter, Sistemas De Medição, Lda, Braga, Portugal |
Veiga, Diana | Enermeter, Sistemas De Medição Lda/ Centro Algoritmi, Univ |
Ferreira, Manuel Joao | Univ. of Minho |
Sandra, Mattos | Cículo Do Coração De Pernambuco, Recife PE, Brazil |
Coimbra, Miguel | Inst. De Telecomunicações / Univ. Do Porto |
Keywords: Ultrasound imaging - Cardiac, Image segmentation, Cardiac imaging and image analysis
Abstract: Echocardiography is an important tool to detect early evidence of mitral valve degradation associated with rheumatic heart disease. The segmentation and tracking of the Anterior Mitral Leaflet helps to quantify the morphologic valve anomalies, such as the leaflet thickening, shape and the mobility changes. The tracking of this leaflet throughout the cardiac cycle is still an open challenge in the research community. The widely used active contours segmentation framework fails when faced with large leaflet displacement. In this work, we propose the integration of optical flow in an open-ended active contour framework to address this difficulty. This additional information promotes solutions with contours next to high leaflet displacements, resulting in superior performance. The algorithm was tested on 9 fully annotated real clinical videos, acquired from the parasternal long axis view. The algorithm is compared with our previous work. Results show a clear improvement in situations where the leaflet exhibits large displacement or irregular shapes, with an average error of 4.5 pixels and a standard deviation of 2 pixels.
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11:50-12:05, Paper FrBT2.5 | Add to My Program |
Automatic Initialization for Active Contour Model in Breast Cancer Detection Utilizing Conventional Ultrasound and Color Doppler |
Keatmanee, Chadaporn | Japan Advanced Inst. of Science and Tech. (JAIST) |
Makhanov, Stanislav | Sirinthorn International Inst. of Tech |
Kazunori, Kotani | Japan Advanced Inst. of Science and Tech. (JAIST) |
Lohitvisate, Wanrudee | Department of Radiology, Thammasat Univ |
Tongvigitmanee, Saowapak | National Electronics and Computer Tech. Center |
Keywords: Ultrasound imaging - Breast
Abstract: Regular examination of breasts may prevent and help to cure because breast cancer is treatable when it is detected early. Therefore, a breast cancer screening modality being sensitivity and cost-effective like ultrasonic imaging modality (US), is strongly required. In addition, the combination of a conventional US and its adjunct, Color Doppler has been proved for decreasing the rate of false-positive in breast cancer diagnosis. Thus, combination of these imaging modalities in a breast cancer segmentation would provide some benefits as well. An effective method for feature segmentation, active contour model has been widely utilized for decades. A crucial stage that affects the performance of active contour model is the initialization. This paper proposes a novel method for an automatic initialization of active contour model designed specifically for US-based imaging modalities. The method estimates an initial contour by utilizing the fusion of conventional US and Color Doppler. Examples and comparisons with three state-of-the-art automatic initialization methods are demonstrated to present the advantages of the proposed method. The evaluation results show high accuracy of initialization as well as fast convergence to features of interest.
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12:05-12:20, Paper FrBT2.6 | Add to My Program |
An Iterative Weighted Method Based on YALL1 for Cone-Beam X-Ray Luminescence Optical Tomography Imaging: A Phantom Experimental Study |
zhao, lili | Shanghai Univ |
jiang, jiehui | Shanghai Univ |
Shu, yuexia | Shanghai Univ |
Yan, Zhuangzhi | Shanghai Univ |
Liu, xin | Shanghai Univ |
Keywords: Optical imaging
Abstract: Abstract—Cone-beam X-ray luminescence optical tomography (CB-XLOT) plays an important role in in vivo small animal imaging study, which can non-invasively image three-dimensional (3-D) distribution of x-ray-excitable nanophosphors deeply embedded in imaged object. However, CB-XLOT suffers from a low spatial resolution due to the ill-posed nature of optical reconstruction. To alleviate the ill-posedness of reconstruction and improve the imaging performance of XLOT, in this paper, we propose an iterative weighted L1 minimization method which is achieved by incorporating YALL1 (Your algorithm for L1 norm problems). The physical phantom experiment was conducted to evaluate the performance of the proposed method, where a custom-made cone-beam XLOT system was used as the imaging platform. The experimental results indicate that by applying the proposed iterative weighted strategy to YALL1 method, the reconstruction performance of XLOT can be improved when compared with the conventional YALL1 method.
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FrBT3 Oral Session, Park Room |
Add to My Program |
MRI Image Reconstruction |
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Chair: Lee, Jongho | Seoul National Univ |
Co-Chair: Qu, Xiaobo | Xaimen Univ |
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10:50-11:05, Paper FrBT3.1 | Add to My Program |
4D Real-Time Phase-Contrast Flow MRI with Sparse Sampling |
Sun, Aiqi | Center for Biomedical Imaging Res. Tsinghua Univ |
Zhao, Bo | Martinos Center for Biomedical Imaging, MGH and Harvard Medical |
Li, Rui | Tsinghua Univ |
Yuan, Chun | Tsinghua Univ. Center of Biomedical Imaging Res. Univ |
Keywords: Magnetic resonance imaging - Image reconstruction, Magnetic resonance imaging - Parallel MRI
Abstract: Conventional phase-contrast (PC) flow MRI provides dynamic information of blood flow by using electro-cardiogram (ECG)-synchronized cine acquisitions and respiration control. However, this often results in relatively low acquisition efficiency and is unable to assess blood flow variabilities. Recently, real-time imaging without ECG gating and respiration control has been a promising technique to overcome these limitations, however, it leads to a significantly more challenging reconstruction problem associated with highlyundersampled data. In this paper, we present a model-based imaging method, which integrates low-rank modeling with parallel imaging, to enable 4D real-time phase-contrast flow MRI without ECG gating and respiration control. The proposed method achieves real-time imaging at a spatial resolution of 2.4 mm, temporal resolution of 35.2 ms, with three directional flow encodings, and well resolves beat-by-beat flow variations, which cannot be achieved by the conventional cine-based method. The proposed has been evaluated by in vivo data with multiple healthy subjects and one arrhythmic patient. For the first time, we demonstrate the feasibility of 4D real-time flow MRI.
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11:05-11:20, Paper FrBT3.2 | Add to My Program |
Fast Dictionary Generation and Searching for Magnetic Resonance Fingerprinting |
Xie, Jun | Hangzhou Normal Univ |
Jian, Zhang | Hangzhou Normal Univ |
Lyu, Mengye | Hong Kong Univ |
Hui, Edward S. | The Univ. of Hong Kong |
Wu, Ed X. | The Univ. of Hong Kong |
Wang, Ze | Temple Univ |
Keywords: Magnetic resonance imaging - Image reconstruction, Image reconstruction - Fast algorithms, Image reconstruction and enhancement - Parametric image reconstruction
Abstract: A super-fast dictionary generation and searching (DGS) algorithm was developed for MR parameter quantification using magnetic resonance fingerprinting (MRF). MRF is a new technique for simultaneously quantifying multiple MR parameters using one temporally resolved MR scan. But it has a multiplicative computation complexity, resulting in a big burden of dictionary generating, saving, and retrieving, which can easily be intractable for any state-of-art computers. Based on retrospective analysis of the dictionary matching object function, a multi-scale ZOOM like DGS algorithm, dubbed as MRF-ZOOM, was proposed. MRF ZOOM is quasi- parameter-separable so the multiplicative computation complexity is broken into additive one. Evaluations showed that MRF ZOOM was hundreds or thousands of times faster than the original MRF parameter quantification method even without counting the dictionary generation time in. Using real data, it yielded nearly the same results as produced by the original method. MRF ZOOM provides a super-fast solution for MR parameter quantification.
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11:20-11:35, Paper FrBT3.3 | Add to My Program |
Parallel Compressive Sensing in a Hybrid Space: Application in Interventional MRI |
Vafay Eslahi, Samira | Texas A&M Univ |
Dhulipala, Pranav Vaidik | Texas A&M Univ |
Shi, Caiyun | Shenzhen Inst. of Advanced Tech. Lauterbur Res. C |
Xie, Guoxi | Shenzhen Inst. of Advanced Tech. Lauterbur Res. C |
Ji, Jim Xiuquan | Texas A&M Univ |
Keywords: Image reconstruction and enhancement - Compressive sensing/sampling, Magnetic resonance imaging - Parallel MRI, Magnetic resonance imaging - Interventional MRI
Abstract: Recently, susceptibility based positive contrast MRI technique emerged as an effective method of visualizing the small MR compatible devices, such as brachytherapy seeds. One of the challenges associated with this method is the long scan time. In this work, we present an accelerated susceptibility based positive contrast MR imaging method, in which the susceptibility map can be generated from an under-sampled data. We use a combination of parallel imaging (GRAPPA) and compressive sensing (CS) technique in a hybrid k-space. The results in brachytherapy seeds imaging show that 3-D high-quality images can be achieved at an acceleration factor up to 4, which can decrease the scan time from 4 minutes to 1.4 minutes.
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11:35-11:50, Paper FrBT3.4 | Add to My Program |
Simultaneous Multislice Magnetic Resonance Fingerprinting with Low-Rank and Subspace Modeling |
Zhao, Bo | MGH/HST Athinoula Martinos Center for Biomedical Imaging, Harvar |
Bilgic, Berkin | Martinos Center for Biomedical Imaging |
Adalsteinsson, Elfar | MIT/MGH Martinos Center |
Griswold, Mark | Case Western Res. Univ |
Wald, Lawrence L. | A. A. Martinos Center for Biomedical Imaging, Dept. of Radiology |
Setsompop, Kawin | Harvard Medical School |
Keywords: Magnetic resonance imaging - Image reconstruction, Image reconstruction and enhancement - Compressive sensing/sampling, Magnetic resonance imaging - Parallel MRI
Abstract: Magnetic resonance fingerprinting (MRF) is a new quantitative imaging paradigm that enables simultaneous acquisition of multiple magnetic resonance tissue parameters (e.g., T1, T2, and spin density). Recently, MRF has been integrated with simultaneous multislice (SMS) acquisitions to enable volumetric imaging with faster scan time. In this paper, we present a new image reconstruction method based on low-rank and subspace modeling for improved SMS-MRF. Here the low-rank model exploits strong spatiotemporal correlation among contrast-weighted images, while the subspace model captures the temporal evolution of magnetization dynamics. With the proposed model, the image reconstruction problem is formulated as a convex optimization problem, for which we develop an algorithm based on variable splitting and the alternating direction method of multipliers. The performance of the proposed method has been evaluated by numerical experiments, and the results demonstrate that the proposed method leads to improved accuracy over the conventional approach. Practically, the proposed method has a potential to allow for a 3x speedup with minimal reconstruction error, resulting in less than 5 sec imaging time per slice.
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11:50-12:05, Paper FrBT3.5 | Add to My Program |
A Low Rank Hankel Matrix Reconstruction Method for Ultrafast Magnetic Resonance Spectroscopy |
Lu, Hengfa | Xiamen Univ |
Zhang, Xinlin | Xiamen Univ |
Qiu, Tianyu | Xiamen Univ |
Yang, Jian | Xiamen Univ |
Guo, Di | Xiamen Univ. of Tech |
Chen, Zhong | Xiamen Univ |
Qu, Xiaobo | Xaimen Univ |
Keywords: Magnetic resonance imaging - MR spectroscopy, Image reconstruction and enhancement - Compressive sensing/sampling, Image reconstruction and enhancement - Parametric image reconstruction
Abstract: Magnetic resonance spectroscopy has many important applications in bio-engineering while acquiring high dimensional spectroscopy is usually time consuming. Non-uniformly sampling can speed up the data acquisition but the missing data points have to be restored with proper signal models. In this work, a specific two dimensional (2D) magnetic resonance signal, in which the first dimension lies in frequency domain while the second dimension lies in time domain, is reconstructed with a proposed low rank Hankel matrix method. This method explores two general properties: 1) the rank of a structured matrix, converted from a 2D exponential signal, is equal to the number of 2D spectral peaks; 2) this rank is small if the spectrum is sparse. Result on realistic magnetic resonance spectroscopy shows that proposed method outperforms the state-of-the-art compressed sensing method on recovering low intensities spectral peaks.
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FrBT4 Invited Session, Min Room |
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Body Sensor Networks – Molecules, Radio, and Machine Learning - II |
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Chair: Balasingham, Ilangko | Oslo Univ. Hospital and Norwegian Univ. of Science and Tech |
Co-Chair: Sugimachi, Masaru | Natl Cardio Center Res. Inst |
Organizer: Balasingham, Ilangko | Oslo Univ. Hospital and Norwegian Univ. of Science and Tech |
Organizer: Anzai, Daisuke | Nagoya Inst. of Tech |
Organizer: Sugimachi, Masaru | Natl Cardio Center Res. Inst |
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10:50-11:05, Paper FrBT4.1 | Add to My Program |
Estimation of Pathlength Travelled by a Capsule Endoscope (I) |
Bjørnevik, Anders | Kongsberg Seatex |
Floor, Pål Anders | NTNU, Gjøvik |
Balasingham, Ilangko | Oslo Univ. Hospital and Norwegian Univ. of Science And |
Keywords: Implantable sensors, Physiological monitoring - Modeling and analysis, Wearable antennas and in-body communications
Abstract: Wireless capsule endoscopy (WCE) is a non-invasive technology used for inspection of the gastrointestinal tract. Localization of the capsule is a vital part of the system enabling physicians to identify the position of anomalies. Due to intestinal motility, the capsule positions will change with time, but the distance travelled in the intestine remains more or less constant. In this paper a method for calculating the pathlength travelled by a WCE is proposed. The method is based on Kalman- and particle filters. The travelled distance was estimated to an accuracy within a few millimeters.
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11:05-11:20, Paper FrBT4.2 | Add to My Program |
Next Generation Body Area Network for Healthcare Application, SmartBAN (I) |
TANAKA, HIROKAZU | HIROSHIMA CITY Univ |
HATAKEYAMA, YASUTAKA | HIROSHIMA CITY Univ |
KOMORI, TATSUYA | TOSHIBA DEVELOPMENT & ENGINEERING Corp |
Matsukuma, Takeshi | Toshiba Development & Engineering Corp |
Keywords: Wearable wireless sensors, motes and systems
Abstract: Recently, wearable vital sensor has been extensively studied and been installed into market. Most of the examples use Bluetooth as a data transmission scheme. European Telecommunication Standard Institute (ETSI) has been standardizing a new BAN standard called SmartBAN aiming at an ultra-low power consumption and co-existence friendly system. In this paper, we present the latest update of the SmartBAN standardization.
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11:20-11:35, Paper FrBT4.3 | Add to My Program |
A Multi-Scale Computational Model of Noninvasive Brain Stimulation: Investigation of Activation of Cortical Neurons (I) |
Seo, Hyeon | Gwangju Inst. of Science and Tech |
Schaworonkow, Natalie | Frankfurt Inst. for Advanced Studies |
Triesch, Jochen | Frankfurt Inst. for Advanced Studies |
KIM, Hyoung-Ihl | Gwangju Inst. of Science and Tech |
Jun, Sung Chan | Gwangju Inst. of Science and Tech |
Keywords: Implantable technologies, Bio-electric sensors - Sensor systems
Abstract: To achieve a better understanding of which cortical excitability is linked to target brain area, we described the effects of noninvasive brain stimulation with transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) and investigated the way to improve the stimulus efficiency in terms of focality and intensity by introducing an implantable transcranial channel. We presented a multi-scale computational model that combines a volume conductor model of the head and multi-compartmental models of cortical neurons to explain the activation of pyramidal neurons in motor cortex. We then simulated neural activations as a function of coil orientation produced by TMS and neural polarizations during tDCS.
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11:35-11:50, Paper FrBT4.4 | Add to My Program |
Flexible Wearable Sensor Nodes with Solar Energy Harvesting |
Wu, Taiyang | Monash Univ |
Arefin, Md Shamsul | Monash Univ |
Redouté, Jean-Michel | Monash Univ |
Yuce, Mehmet | Monash Univ |
Keywords: Wearable power and on-body energy harvesting, Wearable body-compliant, flexible and printed electronics
Abstract: Wearable sensor nodes have gained a lot of attention during the past few years as they can monitor and record people's physical parameters in real time. Wearable sensor nodes can promote healthy lifestyles and prevent the occurrence of potential illness or injuries. This paper presents a flexible wearable sensor system powered by an efficient solar energy harvesting technique. It can measure the subject's heartbeats using a photoplethysmography (PPG) sensor and perform activity monitoring using an accelerometer. The solar energy harvester adopts an output current based maximum power point tracking (MPPT) algorithm, which controls the solar panel to operate within its high output power range. The power consumption of the flexible sensor nodes has been investigated under different operation conditions. Experimental results demonstrate that wearable sensor nodes can work for more than 12 hours when they are powered by the solar energy harvester for 3 hours in the bright sunlight.
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11:50-12:05, Paper FrBT4.5 | Add to My Program |
Comparison of Hand-Craft Feature Based SVM and CNN Based Deep Learning Framework for Automatic Polyp Classification |
Shin, Younghak | NTNU (Norwegian Univ. of Science and Tech |
Balasingham, Ilangko | Oslo Univ. Hospital and Norwegian Univ. of Science And |
Keywords: Image classification, Image feature extraction
Abstract: Colonoscopy is a standard method for screening polyps by highly trained physicians. Miss-detected polyps in colonoscopy are potential risk factor for colorectal cancer. In this study, we investigate an automatic polyp classification framework. We aim to compare two different approaches named hand-craft feature method and convolutional neural network (CNN) based deep learning method. Combined shape and color features are used for hand craft feature extraction and support vector machine (SVM) method is adopted for classification. For CNN approach, three convolution and pooling based deep learning framework is used for classification purpose. The proposed framework is evaluated using three public polyp databases. From the experimental results, we have shown that the CNN based deep learning framework shows better classification performance than the hand-craft feature based methods. It achieves over 90% of classification accuracy, sensitivity, specificity and precision.
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FrBT5 Oral Session, Lee Room |
Add to My Program |
Wearable Sensors and Systems I |
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Chair: Shin, Hangsik | Chonnam National Univ |
Co-Chair: Armentano, Ricardo Luis | Republic Univ |
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10:50-11:05, Paper FrBT5.1 | Add to My Program |
A Wearable Autonomous Heart Rate Sensor Based on Piezoelectric-Charge-Gated Thin-Film Transistor for Continuous Multi-Point Monitoring |
Rasheed, Ahmed | Sun Yat-Sen Univ. (SYSU)-Carnegie Mellon Univ. (CMU) J |
Iranmanesh, Emad | Sysu-Cmu, Jie |
Wang, Kai | Sun Yat-Sen Univ |
Keywords: Physical sensors and sensor systems - New sensing techniques, Physiological monitoring - Instrumentation, Physiological monitoring - Novel methods
Abstract: Autonomous wearable biomedical sensors enable continuous human body vital signs monitoring with features such as being conformable, mobile, cost-effective and self- powered. In this work, we report on an autonomous and multi-positional sensor capable of heart rate and blood pressure monitoring. The device concept is based on a piezoelectric-charge-gated thin-film transistor (PCGTFT) where a polyvinylidene fluoride (PVDF) piezoelectric sandwich structure is incorporated with an amorphous silicon (a- Si:H) dual-gate TFT (DGTFT). An analytical model and preliminary experimental results will be presented along with a demonstration of a proof-of-concept sensing system for continuous multi-point heart rate monitoring.
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11:05-11:20, Paper FrBT5.2 | Add to My Program |
Low Group Delay Signal Conditioning for Wearable Central Blood Pressure Monitoring Device |
Fierro, Germán | Univ. De La Republica |
Silveira, Fernando | Univ. De La Republica |
Armentano, Ricardo Luis | Republic Univ |
Keywords: Physiological monitoring - Instrumentation, Wearable low power, wireless sensing methods
Abstract: Pulse transit time (ptt) is a widely researched approach for wearable, unobtrusive, blood pressure monitoring. The estimation of ptt, being a delay measurement, may be affected by the group delay introduced by the signal conditioning chain. In this work a previously reported method for estimating central (aortic) blood pressure from ptt at aortic domain, using ECG R wave and BCG J wave detection, is considered. A simple design approach for the signal conditioning chain, which is suitable for a wearable device and that takes care of minimizing the impact of eventually introduced spurious delays is presented. The design provides less than 2ms group-delay. The design of a wearable device prototype for ECG, BCG and ptt acquisition and experimental results of its application are reported, showing the effectiveness of the proposed approach.
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11:20-11:35, Paper FrBT5.3 | Add to My Program |
Hemodynamic Sensing of 3D Fingertip Force Using PPG Device on Proximal Part |
Yoshimoto, Shunsuke | Osaka Univ |
Hinatsu, Shun | Osaka Univ |
Kuroda, Yoshihiro | Osaka Univ |
Oshiro, Osamu | Osaka Univ |
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11:35-11:50, Paper FrBT5.4 | Add to My Program |
Tarsusmeter: Development of a Wearable Device for Ankle Joint Impedance Estimation |
Hassan, Modar | Univ. of Tsukuba |
Yagi, Keisuke | Univ. of Tsukuba |
Hsiao, Kaiwen | Univ. of Tsukuba |
Mochiyama, Hiromi | Univ. of Tsukuba |
Suzuki, Kenji | Univ. of Tsukuba |
Keywords: Physical sensors and sensor systems - Mechanical sensors and systems, Integrated wearable and portable systems, Wearable sensor systems - User centered design and applications
Abstract: We present the development and basic evaluation of a new wearable device for estimation of ankle joint impedance called Tarsusmeter. The device is intended for application with persons with locomotion disabilities to quantify the ankle joint impedance, especially in cases of spasticity where the joint's impedance is expected to differ significantly from healthy persons. The lack of a simple and light weight solution to provide objective evaluation of ankle joint impedance motivates the design criteria of this device to be as such. The target application is also to quantify variable stiffness actuator based orthosis in-vivo. Thus the form factor avoids overlap with custom shapes of such orthosis. The paper presents the mechanical design of the device, physical simulations to characterize the device-leg system, the used algorithm for impedance parameter estimation, and preliminary testing of the device.
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11:50-12:05, Paper FrBT5.5 | Add to My Program |
Development of a Smartphone-Based Pulse Oximeter with Adaptive SNR/Power Balancing |
Phelps, Thomas | Univ. of California, San Diego |
Jiang, Haowei | Univ. of California San Diego |
Hall, Drew | Univ. of California, San Diego |
Keywords: Physical sensors and sensor systems - Optical and photonic Sensors and systems, Physiological monitoring - Instrumentation, Portable miniaturized systems
Abstract: Millions worldwide suffer from diseases that exhibit early warnings signs that can be detected by standard clinical-grade diagnostic tools. Unfortunately, such tools are often prohibitively expensive to the developing world leading to inadequate healthcare and high mortality rates. To address this problem, a smartphone-based pulse oximeter is presented that interfaces with the phone through the audio jack, enabling point-of-care measurements of heart rate (HR) and oxygen saturation (SpO2). The device is designed to utilize existing phone resources (e.g., the processor, battery, and memory) resulting in a more portable and inexpensive diagnostic tool than standalone equivalents. By adaptively tuning the LED driving signal, the device is less dependent on phone-specific audio jack properties than prior audio jack-based work making it universally compatible with all smartphones. We demonstrate that the pulse oximeter can adaptively optimize the signal-to-noise ratio (SNR) within the power constraints of a mobile phone (< 10mW) while maintaining high accuracy (HR error < 3.4% and SpO2 error < 3.7%) against a clinical grade instrument.
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12:05-12:20, Paper FrBT5.6 | Add to My Program |
Measurement of Heartbeat Intervals in a Sitting Position Using Multiple Piezoelectric Sensors with Body Movement Reduction |
Igasaki, Tomohiko | Kumamoto Univ |
Shimai, Shogo | Kumamoto Univ |
Kobayashi, Makiko | Kumamoto Univ |
Keywords: Physiological monitoring - Instrumentation, Physical sensors and sensor systems - Mechanical sensors and systems, Mechanical sensors and systems
Abstract: In this study, we proposed a measurement system that extracts heartbeat interval data from multiple piezoelectric sensors placed on a chair that eliminates noise generated by body movement. We asked five healthy males (21−24 years old) to sit in an arbitrary position on a chair that had eight piezoelectric sensors attached, and heartbeat signals were measured. The experiment consisted of four measurements (5 min measurements after adequate rest), while performing specific body movements at a specific time, with deliberately mixed noise of body movements. To remove body movement noise, bandpass filter processing (4 Hz−20 Hz) was applied to the signal obtained from the piezoelectric sensors, and the heartbeat component was extracted using independent component analysis (number of separations was eight) on the processed waveform. For verification, the error rate was obtained before and after the removal of body movement noise, respectively. The error rate after removal of body motion was 2.91 ± 0.75%. In our previous study with two piezoelectric sensors without body movement, the error rate was 2.47 ± 2.66%. Therefore, our proposed measurement system may improve the accuracy of heartbeat interval detection, which can be observed continuously by removing the body motion.
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FrBT6 Invited Session, Zworykin Room |
Add to My Program |
Microfluidic Systems for Cell Manipulation and Analysis |
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Chair: Chen, Weiqiang | New York Univ |
Co-Chair: Lam, Raymond H. W. | City Univ. of Hong Kong |
Organizer: Chen, Weiqiang | New York Univ |
Organizer: Lam, Raymond H. W. | City Univ. of Hong Kong |
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10:50-11:05, Paper FrBT6.1 | Add to My Program |
Nanoplasmon Ruler for Visualizing How Cells “Talk” (I) |
Yang, Wen | Auburn Univ |
Jiacheng, He | Auburn Univ |
Chen, Pengyu | Auburn Univ |
Keywords: Micro- and nano-sensors, Nano-bio technology design, Micro- and nano-technology
Abstract: A novel approach based on the nanoplasmon ruler has been established to achieve direct visualization of the dynamic intercellular communication process in the immune system. Such a novel approach will establish a new paradigm that permits, for the first time, the direct visualization of the dynamic intercellular communication process in the immune system. The knowledge obtained from this study will facilitate a more comprehensive understanding of the immune intercellular network, unlocking the potential to transform the experimental studies into an information-rich science not only in immunology but beyond.
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11:05-11:20, Paper FrBT6.2 | Add to My Program |
Microfluidic Vascularized Microsystem for Probing Inflammation-Biased Angiogenesis (I) |
Cui, Xin | New York Univ |
Morales, Renee-Tyler Tan | New York Univ |
Chen, Weiqiang | New York Univ |
Keywords: Microfluidic applications, Biomaterial-cell interactions - Engineered vascular tissue, Cellular force transduction - Mechanical stimuli and mechanotransduction
Abstract: As the essential parts of circulatory systems, vascular networks have appealed numerous attention in current clinical and translational researches. Engineering vascularized microenvironment models with tunable, multifunctional, and controllable capabilities are important for mimicking in vivo tissue conditions with the controllability in biochemical (e.g. growth factors, cytokines), biophysical (e.g. flow stress, substrate stiffness), intercellular communications (e.g. immune cells, cancer cells) and cell-matrix interactions. We developed a three-dimensional (3D) microfluidic vascularized microsystem integrated with tunable biochemical and biomechanical conditions as well as cell-cell interactions. Using such platform, we investigated the inflammation-biased angiogenesis in a controllable matrix mechanical property, adhesive signature, and biochemical conditions.
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11:20-11:35, Paper FrBT6.3 | Add to My Program |
A Microfluidic Device with Hydrodynamic Trap Arrays for White Blood Cell Counting in Peritoneal Dialysis Solution (I) |
Hwong, Yuh Jen | National Taiwan Univ |
Huang, Nien-Tsu | National Taiwan Univ |
Keywords: Microfluidic applications, Microfluidic techniques, methods and systems
Abstract: Peritoneal dialysis is a treatment for patients who suffer from severe chronic kidney disease. To prevent any infection during the treatment, it is important to monitor the population of white blood cell in dialysis fluid. However, current cell counting techniques usually suffer from labor-intensive manipulation steps and cannot deal with low cell counts. Here, we develop a microfluidic device with hydrodynamic trap arrays to capture neutrophils conjugated with 30μm polystyrene beads and total white blood cell numbers. This microfluidic platform enables simultaneously cell trapping and selection without complicated sample processing steps and equipment. We believe this platform can provide real-time infection status of patient for timely treatment.
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11:35-11:50, Paper FrBT6.4 | Add to My Program |
Microfluidic Eye-Chamber-On-A-Chip for Modeling Oil Emulsification (I) |
Chan, Yau Kei | The Univ. of Hong Kong, Pokfulam Road, Hong Kong |
Shum, Ho Cheung 浩璋 | The Univ. of Hong Kong |
Keywords: Microfluidic applications, Microfluidic techniques, methods and systems
Abstract: Microfluidics, as popularized by the pioneering works of George Whitesides's group at Harvard, has led to many innovative solutions to biomedical applications. The recent advances by groups, such as Prof. Donald Ingber's at Harvard, have shown the possibility to mimic organs in microfluidic chips. In this talk, we will introduce features of a microfluidic chip that we constructed for mimicking the eye chamber. We demonstrate how the chip can be used for modeling the emulsification of oil in the eye following the surgical procedures for treating a type of retinal detachment. I will also discuss some of the recent unpublished works from our group in mimicking the retina.
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11:50-12:05, Paper FrBT6.5 | Add to My Program |
Microfluidic Platforms for Single Cell Studies and Analysis: From Simple Devices to Channel-Less Systems (I) |
Qasaimeh, Mohammad Ameen | New York Univ. Abu Dhabi |
Keywords: Microfluidic applications, Microfluidic techniques, methods and systems, Micro- and nano-technology
Abstract: This talk highlights three different microfluidic platforms for innovative and effective single cell studies and analysis: (1) a microfluidic system for spatiotemporally controlling the delivery of bio-reagents to cells cultured in a microfluidic channel, (2) a microfluidic quadrupole (MQ) formed within an open microfluidic chip to generate floating concentration gradients for cell chemotaxis studies, and (3) a microfluidic platform for isolating circulating plasma cells from multiple myeloma patients’ blood samples.
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12:05-12:20, Paper FrBT6.6 | Add to My Program |
A Microfluidic Multiplex Immunoassay Platform for Quantifying Transient Cytokine Secretions of Immune Cells (I) |
Lam, Raymond H. W. | City Univ. of Hong Kong |
Cui, Xin | New York Univ |
Chen, Weiqiang | New York Univ |
Keywords: Microfluidic applications, Micro- and nano-sensors, Microfluidic techniques, methods and systems
Abstract: We report a microfluidic immunoassay consisting of multiple precise and efficient mixing units for transient multi-cytokine detection secreted by lymphocytes. This device has an array of detection micro-chambers with each included a Taylor dispersion-based mixing unit. The sub-pico-liter bio-samples are extracted from cell culture media and mixed with cytokine-sensitive fluorescence micro-beads, which offer fluorescent signals to quantify the bound cytokines on beads, are embedded in the chambers for quantitative detection of the target cytokines. We optimize the mixing scheme on its robustness and sensitivity. We demonstrate the high detection sensitivity for the detection of multiple cytokine concentrations released by a human leukemic cell line (THP-1). Further development of this device can lead to the profiling of multiple cytokine dynamics of lymphocytes for deeper understandings of the human immune system as well as the immune diseases.
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12:05-12:20, Paper FrBT6.7 | Add to My Program |
Towards Massively Parallelized Individual Cell Manipulations for Next Gen Biopharmaceutical Research (I) |
Jorgolli, Marsela | Amgen Inc |
Keywords: Nano-bio technology design, Microfluidic applications, Micro- and nano-technology
Abstract: Traditional drug-discovery workflows are resource intensive and characterized with long timeliness. Advances in bioprocess technologies, based on automation and miniaturization, have been established to incrementally address these matters – however these technologies are dedicated to specific processes limiting their holistic application. In collaboration with Berkeley Lights Inc. (BLI), Amgen has worked on an innovative nanofluidic tool that couples cellular manipulation via Opto-Electro-Positioning (OEP), fluorescent detection, and software-driven automated workflow execution. The continued development and implementation of this platform will overcome the challenges currently associated with microfluidic, fragmented workflows in biopharma and life science research. The miniaturized automated nanofluidic workflows are transformational and allow massively parallel manipulation of individual cells and reagents.
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FrBT7 Minisymposium, Herrick Room |
Add to My Program |
Rehabilitation Technologies for Neurological Disorders Using
Neuromodulations |
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Chair: Lan, Ning | Shanghai Jiao Tong Univ |
Co-Chair: Niu, Chuanxin M. | Ruijin Hospital, School of Medicine, Shanghai Jiao Tong Univ |
Organizer: Lan, Ning | Shanghai Jiao Tong Univ |
Organizer: Niu, Chuanxin M. | Ruijin Hospital, School of Medicine, Shanghai Jiao Tong Univ |
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10:50-11:05, Paper FrBT7.1 | Add to My Program |
Non-Invasive Peripheral Nerve Stimulation for Tremor Suppression in PD (I) |
Lan, Ning | Shanghai Jiao Tong Univ |
Hao, Manzhao | School of Biomedical Engineering, ShanghaiJiaoTongUniversity |
Hu, Zixiang | Med-X Res. Inst. of Biomedical Engineering, Shang |
Xiao, Qin | Department of Neurology & Inst. of Neurology, Ruijin Hospita |
Keywords: Neural stimulation, Neurological disorders, Neurorehabilitation
Abstract: In this presentation of the minisymposium, a non-invasive technique for suppressing tremor in patients with Parkinson’s disease (PD) by evoked cutaneous afferents using surface electrical stimulation will be discussed. The presentation will introduce the recent findings of spinal neural pathway for tremor signals, and on how the peripheral neuromuscular system interacts with descending tremor signals to generate tremor at limbs. These results led to the proposal and test of a hypothesis that cutaneous afferents can interfere the spinal passage of tremor signals at the propriospinal neuron network, thus causing suppression of tremor amplitude. Here, we report the results obtained in 8 PD patients, which support the above hypothesis.
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11:05-11:20, Paper FrBT7.2 | Add to My Program |
Low-Frequency Bilateral DBS at Subthalamic Nucleus Alters Vocal Responses in Individuals with Parkinson’s Disease (I) |
Niu, Chuanxin M. | Ruijin Hospital, School of Medicine, Shanghai Jiao Tong Univ |
Pan, Yixin | Ruijin Hospital, School of Medicine, Shanghai Jiao Tong Univ |
Li, Dianyou | Ruijin Hospital, School of Medicine, Shanghai Jiao Tong Univ |
Keywords: Neural stimulation - Deep brain, Neurological disorders - Mechanisms, Human performance - Speech
Abstract: Our objective is to study whether and how 60Hz stimulation, compared with 130Hz, affects vocal responses of patients with Parkinson’s Disease (PD). Patients vocalized for 3 seconds with their sound played back to ears in real-time. Individuals with PD, who also received bilateral DBS at STN, sustained a vowel sound (/a/) and received unexpected perturbations in voice loudness auditory feedback. Our results suggest that low-frequency (60Hz) stimulation is likely to differentially affect the vocal response depending on whether the perturbation was augmenting (upshift) or diminishing (downshift) the magnitude of loudness.
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11:20-11:35, Paper FrBT7.3 | Add to My Program |
Deep Brain Stimulation in China (I) |
Li, Luming | Tsinghua Univ |
Keywords: Brain functional imaging - Segmentation
Abstract: Deep brain stimulation (DBS) is the only technique that can directly modulate brain activities using electrical stimulation. A vast amount of research has shown that DBS not only causes a direct effect on the target nuclei, but somehow modulates pathological oscillations that reverberate through multiple brain regions. As such, this provides great opportunities for understanding brain activity in human behaviors. In this talk, the progress of the research and development of DBS in China will be presented, including the device development, applications and innovations. In the last decade, High frequency stimulation (HFS) has been used for the treatment of advanced Parkinson’s disease (PD), which was honored by the Lasker Medical Research Award 2014. However, it is known that HFS is unable to alleviate certain symptoms, such as freezing of gait and dysarthria. We have recently found that the combination of different frequencies can successfully treat these unmanageable symptoms, using our newly developed stimulation therapy called ‘Various Frequency Stimulation (VFS)’. Several cases will be presented in this talk to show the significant differences of VFS to the currently used HFS. From HFS to VFS, a small change but a great deal of difference. There is an enormous challenge in understanding how to modulate the brain? One fact remains is that we need tools and technology. Based on many years’ experience on developing implantable devices, we have established a new platform that not only provides DBS therapy but also gives concurrent measurements of local field potential signals to investigate neural circuits. This research tool is like an implanted brain recorder that may allow us to answer vital questions related with various brain disorders and different brain states in combination with behavioral evaluations. In addition, this device also has great potential for providing high clinical value, such as guiding DBS parameter programming, and finally realizing the in
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FrBT8 Oral Session, Schwan Room |
Add to My Program |
Brain Networks and Connectivity |
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Chair: Barbieri, Riccardo | Pol. Di Milano |
Co-Chair: Choe, Yoonsuck | Texas A&M Univ |
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10:50-11:05, Paper FrBT8.1 | Add to My Program |
Dynamical Brain Connectivity Estimation Using GARCH Models: An Application to Personality Neuroscience |
Riccelli, Roberta | Lab. of Neuromotor Physiology, IRCCS Santa Lucia Foundatio |
Passamonti, Luca | Univ. of Cambridge |
Duggento, Andrea | Univ. of Rome "Tor Vergata" |
Guerrisi, Maria | Univ. of Rome "Tor Vergata" |
Indovina, Iole | Lab. of Neuromotor Physiology, IRCCS Santa Lucia Foundatio |
Terracciano, Antonio | Department of Geriatrics, Florida State Univ. Coll. of Me |
Toschi, Nicola | Univ. of Rome "Tor Vergata", Faculty of Medicine |
Keywords: Functional image analysis, Magnetic resonance imaging - MR neuroimaging
Abstract: It has recently become evident that the functional connectome of the human brain is a dynamical entity whose time evolution carries important information underpinning physiological brain function as well as its disease-related aberrations. While simple sliding window approaches have had some success in estimating dynamical brain connectivity in a functional MRI (fMRI) context, these methods suffer from limitations related to the arbitrary choice of window length and limited time resolution.Recently, Generalized autoregressive conditional heteroscedastic (GARCH) models have been employed to generate dynamical covariance models which can be applied to fMRI. Here, we employ a GARCH-based method (dynamic conditional correlation - DCC) to estimate dynamical brain connectivity in the Human Connectome Project (HCP) dataset and study how the dynamic functional connectivity behaviors related to personality as described by the five-factor model. Openness, a trait related to curiosity and creativity, is the only trait associated with significant differences in the amount of time-variability (but not in absolute median connectivity) of several inter-networkfunctional connections in the human brain. The DCC method offers a novel window to extract dynamical information which can aid in elucidating the neurophysiological underpinning of phenomena to which conventional static brain connectivity estimates are insensitive.
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11:05-11:20, Paper FrBT8.2 | Add to My Program |
Mapping the Full Vascular Network in the Mouse Brain at Submicrometer Resolution |
Lee, Junseok | Texas A&M Univ. Department of Computer Science and Enginee |
An, Wookyung | Texas A&M Univ |
Choe, Yoonsuck | Texas A&M Univ |
Keywords: Image reconstruction - Performance evaluation, Image visualization, Brain image analysis
Abstract: Mapping the microvascular networks in the brain can lead to significant scientific and clinical insights. We developed a serial sectioning microscopy technique called the Knife-Edge Scanning Microscopy (KESM) to section and image the entire mouse brain at submicrometer resolution.In our effort to map the entire vascular network in the mouse brain, we perfused the vessels with India ink and used KESM to image the prepared brain. This results in about 1.5 TB of raw image data which poses a serious challenge in terms of analysis. In this paper, we will present our data set, and computational algorithms we developed to trace and analyze morphological properties of the mouse brain vascular network. Since the data is available across the entire brain in full detail (the smallest capillaries can be observed in our data), it enables the comparison of regional differences in morphological properties. We expect our results to provide rich insights to brain and neuroscience researchers.
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11:20-11:35, Paper FrBT8.3 | Add to My Program |
Dynamic Inter-Network Connectivity in the Human Brain |
Riccelli, Roberta | Lab. of Neuromotor Physiology, IRCCS Santa Lucia Foundatio |
Passamonti, Luca | Univ. of Cambridge |
Duggento, Andrea | Univ. of Rome "Tor Vergata" |
Guerrisi, Maria | Univ. of Rome "Tor Vergata" |
Indovina, Iole | Lab. of Neuromotor Physiology, IRCCS Santa Lucia Foundatio |
Toschi, Nicola | Univ. of Rome "Tor Vergata", Faculty of Medicine |
Keywords: Brain image analysis, Functional image analysis, Magnetic resonance imaging - MR neuroimaging
Abstract: Recently, the field of functional brain connectivity has shifted its attention on studying how functional connectivity (FC) between remote regions changes over time. It is becoming increasingly evident that the human "connectome" is a dynamical entity whose variations are effected over very short timescales and reflect crucial mechanisms which underline the physiological functioning of the brain. In this study, we employ ad-hoc statistical and surrogate data generation methods to quantify whether and which brain networks displayed dynamic behaviors in a very large sample of healthy subjects provided by the Human Connectome Project (HCP). Our findings provided evidences that there are specific pairs of networks and specific networks within the healthy brain that are more likely to display dynamic behaviors. This new set of findings supports the notion that studying the time-variant connectivity in the brain could reveal useful and important properties about brain functioning in health and disease.
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11:35-11:50, Paper FrBT8.4 | Add to My Program |
Resting-State Brain Correlates of Cardiovascular Complexity |
Valenza, Gaetano | Univ. of Pisa |
Duggento, Andrea | Univ. of Rome "Tor Vergata" |
Passamonti, Luca | Univ. of Cambridge |
Diciotti, Stefano | Alma Mater Studiorum, Univ. of Bologna |
Tessa, Carlo | Versilia Hospital, Azienda USL 12 Viareggio |
Toschi, Nicola | Univ. of Rome "Tor Vergata", Faculty of Medicine |
Barbieri, Riccardo | Pol. Di Milano |
Keywords: Functional image analysis, Magnetic resonance imaging - MR neuroimaging
Abstract: While estimates of complex heartbeat dynamics have provided effective prognostic and diagnostic markers for a wide range of pathologies, brain correlates of complex cardiac measures in general and of complex sympatho-vagal dynamics in particular are still unknown. In this study we combine resting state functional Magnetic Resonance Imaging (fMRI) and physiological signal acquisition from 34 healthy subjects selected from the Human Connectome Project (HCP) repository with inhomogeneous point-process approximate and sample heartbeat entropy measures (ipApEn and ipSampEn) to investigate brain areas involved in complex cardiovascular control. Our results show that activity in the Temporal Gyrus, Frontal Orbital Cortex, Temporal Fusiform and Opercular cortices, Planum Temporale, and Paracingulate cortex are negatively correlated with ipApEn dynamics. Activity in the same cortical areas as well as in the Temporal Fusiform cortex are negatively correlated with ipSampEn dynamics. No significant positive correlations were found. These pioneering results suggest that cardiovascular complexity at rest is linked to a few specific cortical brain structures, including crucial areas connected with parasympathetic outflow. This corroborates the hypothesis of a multidimensional central network which controls nonlinear cardiac dynamics under a predominantly vagally-driven tone.
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11:50-12:05, Paper FrBT8.5 | Add to My Program |
Cognitive Control Related Network Analysis a Novel Way to Measure Neuron Fiber Connection of Alzheimer's Disease |
Zhang, Changle | Harbin Inst. of Tech. Shenzhen Graduate School |
Chai, Tao | Harbin Inst. of Tech |
Mao, Shuai | Harbin Inst. of Tech. Shenzhen Graduate School |
Gao, Na | Harbin Inst. of Tech |
Ma, Heather Ting | Harbin Inst. of Tech. Shenzhen Graduate School |
Keywords: Magnetic resonance imaging - Diffusion tensor and diffusion spectrum imaging, Image feature extraction, Brain image analysis
Abstract: Effective measurement of cognitive impairment caused by Alzheimer’s disease (AD) will provide a chance for early medical intervention and delay the disease onset. Diffusion tensor imaging (DTI) provides a non-intrusive examination of cranial nerve diseases which can help us observe the microstructure of neuron fibers. Cognitive control network (CCN) consists of the brain regions that highly related to human self-control. In this study, hub-and-spoke model, which was widely used in transportation and sociology area, was proposed and introduced to analyze the interrelationship of CCN and other regions under its control. At meanwhile, cognitive control related network (CCRN) was built by applying this model. Local and global graph theoretical parameters were calculated and analyzed through statistical method. Significant difference had been found in the scale of local as well as global which may represent the impairment of cognitive control ability. This result may provide a potential bio-marker for the loss of connection caused by Alzheimer’s disease.
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12:05-12:20, Paper FrBT8.6 | Add to My Program |
Resting-State Brain Correlates of Instantaneous Autonomic Outflow |
Valenza, Gaetano | Univ. of Pisa |
Duggento, Andrea | Univ. of Rome "Tor Vergata" |
Passamonti, Luca | Univ. of Cambridge |
Diciotti, Stefano | Alma Mater Studiorum, Univ. of Bologna |
Tessa, Carlo | Versilia Hospital, Azienda USL 12 Viareggio |
Barbieri, Riccardo | Pol. Di Milano |
Toschi, Nicola | Univ. of Rome "Tor Vergata", Faculty of Medicine |
Keywords: Functional image analysis, Magnetic resonance imaging - MR neuroimaging
Abstract: A prominent pathway of brain-heart interaction is represented by autonomic nervous system (ANS) heartbeat modulation. While within-brain resting state networks have been the object of intense functional Magnetic Resonance Imaging (fMRI) research, technological and methodological limitations have hampered research on the central correlates of cardiovascular control dynamics. Here we combine the high temporal and spatial resolution as well as data volume afforded by the Human Connectome Project with a probabilistic model of heartbeat dynamics to characterize central correlates of sympathetic and parasympathetic ANS activity at rest. We demonstrate an involvement of a number of brain regions such as the Insular cortex, Frontal Gyrus, Lateral Occipital Cortex, Paracingulate and Cingulate Gyrus and Precuneous Cortex, as well as subcortical structures (Thalamus, Putamen, Pallidum, Brain-Stem, Hippocampus, Amygdala, and Right Caudate) in the modulation of ANS-mediated cardiovascular control, possibly indicating a broader definition of the central autonomic network (CAN). Our findings provide a basis for an informed neurobiological interpretation of the numerous studies which employ HRV-related measures as standalone biomarkers in health and disease.
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FrBT9 Oral Session, Plonsey Room |
Add to My Program |
Neural Signal Processing I |
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Chair: Li, Haifeng | Harbin Inst. of Tech |
Co-Chair: Santaniello, Sabato | Univ. of Connecticut |
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10:50-11:05, Paper FrBT9.1 | Add to My Program |
A Model Study of the Neural Interaction Via Mutual Coupling Factor Identification |
Zhang, Qichun | Univ. of Essex |
Sepulveda, Francisco | Univ. of Essex |
Keywords: Neural signal processing, Neuromuscular systems - Computational modeling
Abstract: In this paper, an extension of the Hodgkin-Huxley model has been presented to describe the interaction between the nerve fibres. Based on the equivalent electrical circuit, the conductance per unit area between two coupled axons has been introduced as the pairwise coupling factors. Based on the measurement of the membrane potential, these coupling factors can be estimated by linearised identification methods. Therefore, the axon-to-axon interaction can be characterized, which improves the accuracy of the models. Comparing with the simulation studies of the mechanistic model, the presented model is more convenient to be analyzed while the computational complexity has been reduced. Using the presented description, the simulation results indicate that the presented model and the analysis strategy are effective.
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11:05-11:20, Paper FrBT9.2 | Add to My Program |
On Electrophysiological Signal Complexity During Biological Neuronal Network Development and Maturation |
Kapucu, Fikret Emre | Tampere Univ. of Tech |
Vornanen, Inkeri | Tampere Univ. of Tech |
Christophe, Francois | Tampere Univ. of Tech |
Tanskanen, Jarno M. A. | Tampere Univ. of Tech |
Johansson, Julia | Tampere Univ. of Tech |
Mikkonen, Tommi | Tampere Univ. of Tech |
hyttinen, jari | Tampere Univ. of Tech |
Keywords: Neural signal processing
Abstract: Developing neuronal populations are assumed to increase their synaptic interactions and generate synchronized activity, such as bursting, during maturation. These effects may arise from increasing interactions of neuronal populations and increasing simultaneous intra-population activity in developing networks. In this paper, we investigated the neuronal network activity and its complexity by means of self-similarity during neuronal network development. We studied the phenomena using computational neuronal network models and actual in vitro microelectrode array data measured from a developing neuronal network of dissociated mouse cortical neurons. To achieve this, we assessed the spiking and bursting characteristics of the networks, and computed the signal complexity with Sample Entropy. The results show that we can relate increasing simultaneous activity in a neuronal population with decreasing entropy, and track the network development and maturation using this. We can conclude that the complexity of neuronal network signals decreases during the maturation. This can emerge from the fact that as networks mature, they exhibit more synchronous activity, thus decreasing the complexity of its signaling. However, increasing the number of interacting populations has lesser effect on the signal complexity. The entropy based measure provides a tool to assess the complexity of the neuronal network activity, and can be useful in the assessment of developing networks or the effects of drugs and toxins on their functioning.
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11:20-11:35, Paper FrBT9.3 | Add to My Program |
Nonmotor Regions Encode Path-Related Information During Movements |
Breault, Macauley S. | Johns Hopkins Univ |
Sacré, Pierre | Johns Hopkins Univ |
Johnson, Jacob J. | Indian Inst. of Tech. Guwahati |
Kerr, Matthew | Johns Hopkins Univ |
Johnson, Matthew | Cleveland Clinic |
Bulacio, Juan | Cleveland Clinic |
Gonzalez-Martinez, Jorge | Cleveland Clinic |
Sarma, Sridevi V. | Johns Hopkins Univ |
Gale, John | Cleveland Clinic |
Keywords: Neural signal processing, Human performance - Sensory-motor, Brain functional imaging - Source localization
Abstract: Sensorimotor control and the involvement of motor brain regions has been extensively studied, but the role nonmotor brain regions play during movements has been overlooked. This is particularly due to the difficulty of recording from multiple regions in the brain during motor control. In this study, we utilize stereoelectroencephalography (SEEG) recording techniques to explore the role nonmotor brain areas have on the way we move. Nine humans were implanted with SEEG depth electrodes for clinical purposes, which rendered access to local field potential (LFP) activity in deep and peripheral nonmotor structures. Participants performed fast and slow arm reaching movements using a robotic manipulandum. In this study, we explored whether neural activity in a given nonmotor brain structure correlated to movement path metrics including: path length, path deviation, and path speed. Statistical analysis revealed correlations between averaged neural activity in middle temporal gyrus, supramarginal gyrus, and fusiform gyrus and our path metrics both within and across the subjects. Furthermore, we split trials across subjects into two groups: one group consisted of trials with high values of each path metric and the other with low values. We then found significant differences in LFP power in specific frequency bands (e.g. beta) during movement between each group. These results suggest that nonmotor regions may dynamically encode path-related information during movement.
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11:35-11:50, Paper FrBT9.4 | Add to My Program |
Importance of Vesicle Release Stochasticity in Neuro-Spike Communication |
Ramezani, Hamideh | Koc Univ |
Akan, Ozgur B. | Koc Univ |
Keywords: Neural signal processing, Neural signals - Information theory
Abstract: Aim of this paper is proposing a stochastic model for vesicle release process, a part of neuro-spike communication. Hence, we study biological events occurring in this process and use microphysiological simulations to observe functionality of these events. Since the most important source of variability in vesicle release probability is opening of voltage dependent calcium channels (VDCCs) followed by influx of calcium ions through these channels, we propose a stochastic model for this event, while using a deterministic model for other variability sources. To capture the stochasticity of calcium influx to presynaptic neuron in our model, we study its statistics and find that it can be modeled by a distribution defined based on Normal and Logistic distributions.
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11:50-12:05, Paper FrBT9.5 | Add to My Program |
Music-Evoked Emotion Classification Using EEG Correlation-Based Information |
Bo, Hongjian | Harbin Inst. of Tech |
Ma, Lin | Harbin Inst. of Tech |
Li, Haifeng | Harbin Inst. of Tech |
Keywords: Neural signal processing, Brain functional imaging - EEG, Brain-computer/machine interface
Abstract: The relation between music and emotions has been investigated for decades. Most of the studies focused on short clips and were designed with specific tasks. This paper investigated the emotional states from electroencephalogram (EEG) activities during music appreciation. An emotion evoked experiment paradigm was designed during music appreciation. The EEG signals were recorded in 15 healthy adults during the entire process of music listening. The band power change (BPC) and higher order crossing (HOC) features were extracted from the EEG signals. A correlation-based feature analysis approach was proposed to find the most relevant features in time, frequency and channel space domains. From the results, this method achieved the average accuracy of 67.2% for the classification of high and low valence in the combination of BPC and HOC features. A deeper understanding of the brain emotional patterns could be helpful in building an intelligent and friendly affective application.
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12:05-12:20, Paper FrBT9.6 | Add to My Program |
Effects of the Temporal Pattern of Subthalamic Deep Brain Stimulation on the Neuronal Complexity in the Globus Pallidus |
Deng, Callie | Johns Hopkins Univ |
Sun, Tony | Los Altos High School |
Zhang, Manning | Johns Hopkins Uniersity |
Gale, John | Cleveland Clinic |
Montgomery, Erwin | Univ. of Alabama at Birmingham |
Santaniello, Sabato | Univ. of Connecticut |
Keywords: Neural signal processing, Neural stimulation - Deep brain, Neurological disorders
Abstract: Deep brain stimulation (DBS) is a surgical treatment for Parkinson's disease (PD) but, despite clinical efficacy, the mechanisms of DBS still require investigation. Recent evidence suggests that the temporal pattern of the electrical pulses may be critical to the therapeutic merit of DBS and carefully-designed, non-regular patterns could ameliorate some of the motor symptoms in PD. It is unclear, though, how different stimulation patterns affect the neural activity in the basal ganglia and whether this is related to the pathophysiology of PD. In this study, a non-human primate was treated with DBS of the subthalamic nucleus while single-unit recordings were collected in the animal’s globus pallidus internus (GPi). Three stimulation patterns were applied (one regular, two non-regular) and the stimulation effects on the GPi spike trains were assessed via point process modeling. On a preliminary set of 23 GPi neurons, we show that regular DBS maximized the neuronal complexity, which is a measure of the amount of information that a single neuron can encode, and significantly increased the dependency of the neurons' spike trains on the background ensemble activity through an articulated balance of excitation and inhibition. Overall, regular DBS caused the largest modulation in the neurons’ spiking pattern and the largest increment in encoding capabilities. Both results may be relevant to the mechanisms of therapeutic DBS.
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FrBT10 Oral Session, Schmitt Room |
Add to My Program |
General and Theoretical Informatics - Deep Learning and Big Data to
Knowledge |
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Chair: Nguyen, Hung T. | Univ. of Tech. Sydney |
Co-Chair: Minhas, Atul Singh | Univ. of Liverpool |
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10:50-11:05, Paper FrBT10.1 | Add to My Program |
A Separated Feature Learning Based DBN Structure for Classification of SSMVEP Signals |
Jia, Yaguang | Xi'an Jiaotong Univ |
Xie, Jun | Xi'an Jiaotong Univ |
Xu, Guanghua | Xi'an Jiaotong Univ |
Li, Min | School of Mechanical Engineering, Xi’an Jiaotong Univ |
Zhang, Sicong | Xi’an Jiaotong Univ |
Luo, Ailing | Xi’an Jiaotong Univ |
Han, Xingliang | Xi’an Jiaotong Univ |
Keywords: General and theoretical informatics - Deep learning and big data to knowledge, Sensor Informatics - Multi-sensor data fusion
Abstract: Signal processing is one of the key points in brain computer interface (BCI) application. The common methods in BCI signal classification include canonical correlation analysis (CCA), support vector machine (SVM) and so on. However, because BCI signals are very complex and valid signals often come with confounded background noise, many current classification methods would lose meaningful information embedded in human EEGs. Otherwise, due to the huge inter-subject variability with respect to characteristics and patterns of BCI signals, there often exists large difference of classification accuracy among different subjects. Since BCI signals have high dimensionality and multi-channel properties, this paper proposes a novel structure of deep belief neural (DBN) network stacked by restricted boltsman machine (RBM) to extract efficient features from steady-state motion visual evoked potential signals and implement further classification. Here DBN extracts local feature from BCI data of each channel separately and fuses the local features, and then input the fused features to the output classifier which is consist of softmax units. Results proved that the proposed algorithm could achieve higher accuracy and lower inter-subject variability in short response time when compared to conventional CCA method.
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11:05-11:20, Paper FrBT10.2 | Add to My Program |
The Obesity Paradox in ICU Patients |
Pan, Janice | The Univ. of Texas at Austin |
Shaffer, Robert | The Univ. of Texas at Austin |
Sinno, Zeina | The Univ. of Texas at Austin |
Tyler, Marcus | The Univ. of Texas at Austin |
Ghosh, Joydeep | Univ. of Texas at Austin |
Keywords: General and theoretical informatics - Big data analytics, General and theoretical informatics - Causality analysis and case-based reasoning, Bioinformatics - Bioinformatics databases
Abstract: Excessive weight is connected with an increased risk of certain life-threatening diseases. However, some evidence shows that among patients with chronic diseases such as heart failure (HF) chronic kidney disease (CKD) and COPD, increased weight is paradoxically associated with a decreased risk of mortality. This counterintuitive phenomenon is referred to as the obesity paradox. The obesity paradox has been mostly observed among certain cohorts of patients with HF, but not specific to patients in the Intensive Care Unit (ICU) setting. This paper studies the relationship between obesity and mortality of ICU patients with and without HF and presents evidence supporting the existence of this paradox. The results provide helpful insights for developing more patient-centric care in ICUs. Additionally, we use both the MIMIC-II and (recently available) MIMIC-III databases, for which few comparative studies exist to date. We demonstrate an aspect of consistency between the databases, providing a significant step towards validating the use of the newly announced MIMIC-III in broader studies.
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11:20-11:35, Paper FrBT10.3 | Add to My Program |
Automated Embolic Signal Detection Using Deep Convolutional Neural Network |
Sombune, Praotasna | Thammasat Univ |
Phienphanich, Phongphan | Thammasat Univ |
Phuechpanpaisal, Sutanya | Thammasat Univ |
Muengtaweepongsa, Sombat | Thammasat Univ |
Ruamthanthong, Anuchit | Radiology Department Phramongkutklaow Hospitalbangkok |
Tantibundhit, Charturong | Thammasat Univ |
Keywords: General and theoretical informatics - Deep learning and big data to knowledge, General and theoretical informatics - Machine learning, General and theoretical informatics - Decision support systems
Abstract: This work investigated the potential of Deep Neural Network in detection of cerebral embolic signal (ES) from transcranial Doppler ultrasound (TCD). The resulting system is aimed to couple with TCD devices in diagnosing a risk of stroke in real-time with high accuracy. The Adaptive Gain Control (AGC) approach developed in our previous study is employed to capture suspected ESs in real-time. By using spectrograms of the same TCD signal dataset as that of our previous work as inputs and the same experimental setup, Deep Convolutional Neural Network (CNN), which can learn features while training, was investigated for its ability to bypass the traditional handcrafted feature extraction and selection process. Extracted feature vectors from the suspected ESs are later determined whether they are of an ES, artifact (AF) or normal (NR) interval. The effectiveness of the developed system was evaluated over 19 subjects going under procedures generating emboli. The CNN-based system could achieve in average of 83.0% sensitivity, 80.1% specificity, and 81.4% accuracy, with considerably much less time consumption in development. The certainly growing set of training samples and computational resources will contribute to high performance. Besides having potential use in various clinical ES monitoring settings, continuation of this promising study will benefit developments of wearable applications by leveraging learnable features to serve demographic differentials.
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11:35-11:50, Paper FrBT10.4 | Add to My Program |
A CHF Detection Method Based on Deep Learning with RR Intervals |
Chen, Wenhui | Univ. of Tech. Sydney |
Liu, Guan-Zheng | Shenzhen Inst. of Advanced Tech |
Su, Steven Weidong | Univ. of Tech. Sydney |
Jiang, Qing | Sun Yat-Sen Univ |
Nguyen, Hung T. | Univ. of Tech. Sydney |
Keywords: General and theoretical informatics - Deep learning and big data to knowledge, Health Informatics - Patient tracking, Health Informatics - Informatics for chronic disease management
Abstract: There are extensive studies investigating congestive heart failure (CHF) detection based on heart rate variability. Although a high level of accuracy has been achieved, its robustness under different conditions is not guaranteed. To improve the robustness, we applied sparse auto-encoder-based deep learning algorithm in CHF detection with RR intervals. A total data size of 30,592 (5-min RR interval) was obtained from 72 healthy persons and 44 CHF patients. The deep learning algorithm first extracts unsupervised features using a sparse auto-encoder from raw RR intervals, then constructs a deep neural network model with various hidden nodes combinations. Results showed that the model achieved 72.41% accuracy. This demonstrated that RR intervals have potential in CHF detection but cannot fully reflect dynamic change in 24-h.
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11:50-12:05, Paper FrBT10.5 | Add to My Program |
DeepDeath: Learning to Predict the Underlying Cause of Death with Big Data |
Hassanzadeh, Hamid | Georgia Inst. of Tech |
Wang, May D. | Georgia Tech. and Emory Univ |
Sha, Ying | Georgia Inst. of Tech |
Keywords: General and theoretical informatics - Deep learning and big data to knowledge, Health Informatics - Decision support methods and systems, General and theoretical informatics - Big data analytics
Abstract: Multiple cause of death data provides a valuable source of information that can be used to enhance health standards by predicting health related trajectories in societies with large populations. These data are often available in large quantities across U.S. states and require Big Data techniques to uncover complex patterns that are hidden in them. We design two different classes of models suitable for large-scale analysis of mortality data, a Hadoop based ensemble of random forests trained over N-grams, and the DeepDeath, a deep classifier based on recurrent neural networks paradigm. We apply both classes to the mortality data provided by the National Center for Health Statistics and show that while both perform significantly better than the random classifier, the deep model that utilizes long short-term memory networks (LSTMs), surpasses the N-gram based models and is capable of learning the temporal aspect of the data without a need for building ad-hoc, expert-driven features.
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12:05-12:20, Paper FrBT10.6 | Add to My Program |
Automated Vision-Based Analysis of Levodopa-Induced Dyskinesia with Deep Learning |
Li, Michael Hong Gang | Univ. of Toronto |
Mestre, Tiago | Ottawa Hospital Res. Inst |
Fox, Susan | Univ. of Toronto |
Taati, Babak | Toronto Rehabilitation Inst. and Univ. of Toronto |
Keywords: General and theoretical informatics - Deep learning and big data to knowledge, General and theoretical informatics - Artificial Intelligence, Sensor Informatics - Wireless sensors and systems
Abstract: Levodopa is the gold standard therapy for Parkinson’s disease (PD), but its prolonged usage leads to additional motor complications, namely levodopa-induced dyskinesia (LID). To assess LID and adjust drug regimens for optimal relief, patients attend regular clinic visits. However, the intermittent nature of these visits can fail to capture important changes in a person’s condition. With the recent emergence of deep learning achieving impressive results in a wide array of fields including computer vision, there is an opportunity for video analysis to be used for automated assessment of LID. Deep learning for pose estimation was studied as a viable means of extracting body movements from PD assessment videos. Movement features were computed from joint trajectories. Results show that features derived from vision-based analysis have moderate to good correlation with clinician ratings of dyskinesia severity. This study presents the first application of deep learning to video analysis in PD, and demonstrates promise for future development of a non-contact system for objective PD assessment.
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FrBT11 Oral Session, Greatbatch Room |
Add to My Program |
Cardiovascular Simulations |
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Chair: Shim, Eun Bo | Kangwon National Univ |
Co-Chair: Chbat, Nicolas W. | Center of Excellence in Critical Care Innovation |
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10:50-11:05, Paper FrBT11.1 | Add to My Program |
Pilot Study on Vascular Intervention Training Based on Blood Flow Effected Guidewire Simulation |
Cai, Jiayin | School of Biomedical Engineering, Shanghai Jiao Tong Univ |
Xie, Hongzhi | Peking Union Medical Coll. Hospital |
Zhang, Shuyang | Peking Union Medical Coll. Hospital |
Gu, Lixu | Shanghai Jiaotong Univ |
Keywords: Cardiac catheterization, Cardiovascular and respiratory system modeling - Blood flow models
Abstract: A decent guidewire behavior simulation is vital to the virtual vascular intervention training. The influence of blood flow has rarely been taken into consideration in former works of guidewire simulation. This paper addresses the problem by integrating blood flow analysis and proposes a novel guidewire simulation model. The blood flow distribution inside arterial vasculature is computed by separating the vascular model into discrete cylindrical vessels and modeling the flow in each vessel with the Poiseuille Law. The blood flow computation is then integrated into a Kirchhoff rods model. The simulation could be run in real time with hardware acceleration at least 30 fps. To validate the result, an experiment environment with a 3D printed vascular phantom and an electromagnetic tracking(EMT) system was set up with clinical-used guidewire sensors applied in phantom to trace its motion as the standard for comparison. Experiment results reveal that the shown blood flow effected model presents better physical credibility with a lower and more stable root-mean-square(RMS) at 2.14mm±1.24mm, better than the Kirchhoff model of 4.81mm±3.80mm.
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11:05-11:20, Paper FrBT11.2 | Add to My Program |
Applying Computer Simulation to the Design of Flow-Diversion Treatment for Intracranial Aneurysms |
Zhang, Mingzi | Tohoku Univ |
Li, Yujie | Tohoku Univ |
Verrelli, David I. | Macquarie Univ |
Chong, Winston | Interventional Neuroradiology Unit, Department of Diagnostic Ima |
Ohta, Makoto | Univ. of Tohoku |
Qian, Yi | Macquarie Univ |
Keywords: Vascular mechanics and hemodynamics - Vascular Disease, Vascular mechanics and hemodynamics - Vascular Hemodynamics
Abstract: Although flow-diversion (FD) treatment has been proven to be able to induce intracranial aneurysm (IA) occlusion, clinical follow-ups reported that a number of patients may still suffer from delayed IA rupture or incomplete aneurysm occlusion post-treatment. Complete aneurysm occlusion is believed to be associated with favourable haemodynamic alteration post-treatment, which may be greatly affected by the selection of device size and quantity, as well as the FD deployment procedure. However, clinicians have to choose and deploy the FD relying on their experience, since no post-stenting haemodynamic information is generally available to them prior to a specific treatment. In this study, using a virtual FD deployment technique and computational fluid dynamics method, we demonstrate and compare the haemodynamic changes after virtual FD treatments using a variety of prospective treating strategies.
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11:20-11:35, Paper FrBT11.3 | Add to My Program |
A Sensitivity Study on Modelling a Flow-Diverting Stent As a Porous Medium Using Computational Fluid Dynamics |
Li, Yujie | Tohoku Univ |
Zhang, Mingzi | Tohoku Univ |
Verrelli, David I. | Macquarie Univ |
Yang, William | Mineral Res. CSIRO |
Chong, Winston | Interventional Neuroradiology Unit, Department of Diagnostic Ima |
Ohta, Makoto | Univ. of Tohoku |
Qian, Yi | Macquarie Univ |
Keywords: Vascular mechanics and hemodynamics - Vascular Disease, Vascular mechanics and hemodynamics - Vascular Hemodynamics
Abstract: The flow-diverting (FD) stent has become a commonly used endovascular device to treat cerebral aneurysms. This discourages blood from entering the aneurysm, thereby reducing the likelihood of aneurysm rupture. Using computational fluid dynamics (CFD) to simulate the aneurysmal haemodynamics after FD treatment could help clinicians predict the stent effectiveness prior to the real procedure in the patient. As an alternative to modelling the stent as a fine wire mesh, modelling the FD stent as a porous medium was established to save computational time, and has also been proved capable of predicting the same haemodynamics as obtained using the real FD stent geometry. The flow resistance effect of a porous-medium stent may differ with respect to its morphology or permeability; however, the flow resistance effect after adjusting these parameters had not been clarified. In this study, we analysed the haemodynamic changes caused by alterations of porous-medium thickness and permeability, thereby providing future porous-medium stent simulations with important information on the respective parametric sensitivities. We found significant sensitivity to permeability. Results were insensitive to thickness when permeability was adjusted beforehand to compensate. We also compared our results with observations from an in-vitro model, and found good agreement. This supports adoption of porous-medium models in future work.
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11:35-11:50, Paper FrBT11.4 | Add to My Program |
An HMM-Based Recognition Framework for Endovascular Manipulations |
Zhou, Xiaohu | Inst. of Automation, Chinese Acad. of Sciences |
Bian, Gui-Bin | Inst. of Automation, Chinese Acad. of Sciences |
Xie, Xiao-Liang | Chinese Acad. of Sciences |
Hou, Zeng-Guang | Inst. of Automation, Chinese Acad. of Sciences |
Keywords: Cardiac catheterization, Cardiovascular and respiratory system modeling - Cardiovascular Disease, Coronary artery disease
Abstract: Robotic surgical systems are becoming increasingly popular for the treatment of cardiovascular diseases. However, most of them have been designed without considering techniques and skills of natural surgical manipulations, which are key factors to clinical success of percutaneous coronary intervention. This paper proposes an HMM-based framework to recognize six typical endovascular manipulations for surgical skill analysis. A simulative surgical platform is built for endovascular manipulations assessed by five subjects (1 expert and 4 novices). The performances of the proposed framework are evaluated by three experimental schemes with the optimal model parameters. The results show that endovascular manipulations are recognized with high accuracy and reliable performance. Furthermore, the acceptable results can also be applied to the design of next generation vascular interventional robots.
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11:50-12:05, Paper FrBT11.5 | Add to My Program |
Effect of Catheter Positions on Hemodynamics and Coil Formation after Coil Embolization |
Fujimura, Soichiro | Tokyo Univ. of Science |
Takao, Hiroyuki | Jikei Univ. School of Medicine |
Suzuki, Takashi | Tokyo Univ. of Science |
Dahmani, Chiheb | Tech. Univ. of Munich |
Mamori, Hiroya | Tokyo Univ. of Science |
Fukushima, Naoya | Tokyo Univ. of Science |
Yamamoto, Makoto | Tokyo Univ. of Science |
Murayama, Yuichi | Jikei Univ. School of Medicine |
Keywords: Vascular mechanics and hemodynamics - Vascular Hemodynamics, Vascular mechanics and hemodynamics - Vascular Disease, Vascular mechanics and hemodynamics - Vascular mechanics
Abstract: Coil embolization using a micro catheter and coils is one of the most popular surgical methods used for treating intracranial aneurysms. This method is minimally invasive, however, recanalization remains a major problem. To prevent aneurysmal recanalization, surgeons need to better understand the effects of changing catheter position because this is under their control during operations. However, our latest study only considered a sidewall-type aneurysm and the tip of the catheter was always placed at the center of the aneurysm. There are no other studies that use FEM and CFD to investigate the ideal catheter position for effective coil embolization. In this study, we use the finite element method and computational fluid dynamics to simulate coil embolization. A basic bifurcation-type aneurysm model was created and the embolic coil was modeled based on actual Stryker Target 360 Soft Coils. We evaluated the reduction in velocity after embolization and the distance of the embolized coil’s center of gravity from the center of the aneurysm while changing the catheter tip position. The results of this study indicate that the formations of the embolized coil took multifarious shapes when the catheter position was changed. Although the flows are reduced after the embolism in all cases, the percentage of velocity reduction completely differs for each case. We also observed a relationship between the velocity reduction and neck volume embolization ratio (NVER) with a correlation coefficient of 0.912. In addition, the relations between the Z-coordinate of the catheter tip and rCG shows a linear regression with a correlation coefficient of 0.750. The neck volume embolization ratio is also important for effective velocity reduction in both bifurcation-type and sidewall-type aneurysms. In addition, it is useful to set the catheter tip at the bottom of the aneurysms to deploy the first coil as a flaming coil.
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12:05-12:20, Paper FrBT11.6 | Add to My Program |
Effects of Septum and Pericardium on Heart-Lung Interactions in a Cardiopulmonary Simulation Model |
Karamolegkos, Nikolaos | Columbia Univ |
Albanese, Antonio | Philips Res. North America |
Chbat, Nicolas W. | Center of Excellence in Critical Care Innovation |
Keywords: Cardiovascular and respiratory system modeling - Cardiovascular-Respiratory Interactions, Cardiovascular and respiratory system modeling - Cardiac models, Cardiovascular and respiratory system modeling - Compartmental modeling
Abstract: Mechanical heart-lung interactions are often overlooked in clinical settings. However, their impact on cardiac function can be quite significant. Mechanistic physiology-based models can provide invaluable insights into such cardiorespiratory interactions, which occur not only under external mechanical ventilatory support but in normal physiology as well. In this work, we focus on the cardiac component of a previously developed mathematical model of the human cardiopulmonary system, aiming to improve the model's response to the intrathoracic pressure variations that are associated with the respiratory cycle. Interventricular septum and pericardial membrane are integrated into the existing model. Their effect on the overall cardiac response is explained by means of comparison against simulation results from the original model as well as experimental data from literature.
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FrBT14 Oral Session, Schaldach Room |
Add to My Program |
Image Segmentation I |
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Chair: Chang, Herng-Hua | National Taiwan Univ |
Co-Chair: Xia, Zeyang | Shenzhen Inst. of Advanced Tech. Chinese Acad. of Sciences |
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10:50-11:05, Paper FrBT14.1 | Add to My Program |
Volumetric Analysis of Respiratory Gated Whole Lung and Liver CT Data with Motion-Constrained Graph Cuts Segmentation |
Cha, Jung won | Univ. of Louisville |
Farhangi, Mohammad Mehdi | Univ. of Louisville |
Dunlap, Neal | Univ. of Louisville, Louisville |
Amini, Amir | Univ. of Louisville |
Keywords: Image segmentation, X-ray CT imaging
Abstract: The conventional graph cuts technique has been widely used for image segmentation due to its ability to find the global minimum and its ease of implementation. However, it is an intensity-based technique and as a result is limited to segmentation applications where there is significant contrast between the object and the background. We modified the conventional graph cuts method by adding shape prior and motion information. Active shape models (ASM) with signed distance functions were used to capture the shape prior information, preventing unwanted surrounding tissue from becoming part of the segmented object. The optical flow method was used to estimate the local motion and to extend 3D segmentation to 4D by warping a prior shape model through time. The method has been applied to segmentation of whole lung boundary and whole liver boundary from respiratory gated CT data. 4D lung boundary segmentation in five patients, and 4D liver boundary segmentation in five patients were performed and in each case, results were compared with the results from expert-delineated ground truth. 4D segmentation for five phases of CT data took approximately ten minutes on a PC workstation with AMD Phenom II and 32GB of memory. An important by-product is quantitative whole organ volumes from respiratory gated CT from end-inspiration to end-expiration which can be determined with high accuracy.
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11:05-11:20, Paper FrBT14.2 | Add to My Program |
Development of a Radiobiological Evaluation Tool to Assess the Expected Clinical Impacts of Contouring Accuracy between Manual and Semi-Automated Segmentation Algorithms |
Kim, Yusung | Department of Radiation Oncology, the Univ. of Iowa, Iowa C |
Patwardhan, Kaustubh | The Univ. of Iowa |
Beichel, Reinhard | The Univ. of Iowa |
Smith, Brian | Univ. of Iowa |
Mart, Christopher | Medical Univ. of South Carolina |
Plichta, Kristin | Univ. of Iowa |
tangel, Chang | Case Western Res. Univ |
Sonka, Milan | Univ. of Iowa |
Graham, Michael | Univ. of Iowa |
Magnotta, Vincent Alfonso | Univ. of Iowa |
Casavant, Benjamin | Univ. of Wisconsin-Madison |
Xia, Junyi | Univ. of Iowa |
Buatti, John | Department of Radiation Oncology, the Univ. of Iowa, Iowa C |
Keywords: Image segmentation, Multivariate image analysis, Functional image analysis
Abstract: RADEval is a tool developed to assess the expected clinical impact of contouring accuracy when comparing manual contouring and semi-automated segmentation. The RADEval tool, designed to process large scale datasets, imported a total of 2,760 segmentation datasets, along with a Simultaneous Truth and Performance Level Estimation (STAPLE) to act as ground truth tumor segmentations. Virtual dose-maps were created within RADEval and two different tumor control probability (TCP) values using a Logistic and a Poisson TCP models were calculated in RADEval using each STAPLE and each dose-map. RADEval also virtually generated a ring of normal tissue. To evaluate clinical impact, two different uncomplicated TCP (UTCP) values were calculated in RADEval by using two TCP-NTCP correlation parameters (δ= 0 and 1). NTCP values showed that semi-automatic segmentation resulted in lower NTCP with an average 1.5 – 1.6 % regardless of STAPLE design. This was true even though each normal tissue was created from each STAPLE (p < 0.00001). TCP and UTCP presented no statistically significant differences (p ≥ 0.1884). The intra-operator standard deviations (SDs) for TCP, NTCP and UTCP were significantly lower for the semi-automatic segmentation method regardless of STAPLE design (p < 0.0331). Both intra-and inter-operator SDs of TCP, NTCP and UTCP were significantly lower for semi-automatic segmentation for the STAPLE 1 design (p <0.0331). RADEval was able to efficiently process 4,920 datasets of two STAPLE designs and successfully assess the expected clinical impact of contouring accuracy.
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11:20-11:35, Paper FrBT14.3 | Add to My Program |
Angled Tooth Segmentation from Computerized Tomography Images |
Gan, Yangzhou | Shenzhen Inst. of Advanced Tech. Chinese Acad. of S |
Xia, Zeyang | Shenzhen Inst. of Advanced Tech. Chinese Acad. of S |
Xiong, Jing | Shenzhen Inst. of Advanced Tech. Chinese Acad. of S |
Zhou, Xinwen | Shanghai Jiao Tong Univ |
Li, Guanglin | Shenzhen Inst. of Advanced Tech |
Zhao, Qunfei | Shanghai Jiao Tong Univ |
Keywords: Image segmentation
Abstract: Tooth contour segmentation from dental computerized tomography (CT) images is one of the fundamental steps in reconstructing the three-dimensional models of teeth. However, existing methods depend on the tooth shape similarity between adjacent slices, and have difficulty to segment these angled teeth whose contour shapes from adjacent slices may differ a lot. This study proposes a new method for contour segmentation of angled teeth from CT images. The volume of interest (VOI) of target tooth and corresponding tooth axis are first extracted from volumetric CT images. Local images within the VOI of target tooth are then rotated such that the tooth axis in the rotated images is perpendicular to the transverse section. Tooth contours are finally segmented from the rotated images using a hybrid level set model slice-by-slice. Experimental results verified that the proposed method was effective to segment contours of angled teeth from CT images.
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11:35-11:50, Paper FrBT14.4 | Add to My Program |
Automatic Measurement of Fetal Nuchal Translucency from Three-Dimensional Ultrasound Data |
Nie, Siqing | Fudan Univ |
Yu, Jinhua | Fudan Univ |
Chen, Ping | First Maternity and Infant Hospital |
Wang, Yuanyuan | Fudan Univ |
Guo, Yi | Fudan Univ |
Zhang, Jianqiu | Fudan Univ |
Keywords: Image segmentation
Abstract: The Nuchal translucency (NT), which is the collection of fluid at the back of the fetal neck, is related to chromosomal defects and early cardiac failure in first trimester of pregnancy. In clinic, the thickness of NT is used as an important marker in prenatal screening, and is manually measured by sonographers in the mid-sagittal plane. In this paper, an automatic method based on dynamic programming is proposed to detect the thickness and area of NT in the mid-sagittal plane. Furthermore, the volume of NT in the whole three-dimensional ultrasound data is also measured. A novel cost function for dynamic programming is proposed and results in higher accuracy of NT border detection. As the nuchal translucency is the collection fluid part, higher dimensional markers of NT possess more potential to represent the amount of the fluid.
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11:50-12:05, Paper FrBT14.5 | Add to My Program |
Brain Segmentation in MR Images Using a Texture-Based Classifier Associated with Mathematical Morphology |
Chang, Herng-Hua | National Taiwan Univ |
Hsieh, Chih-Chung | National Taiwan Univ |
Keywords: Image segmentation, Brain image analysis, Image feature extraction
Abstract: Skull stripping, which refers to the segmentation of brain tissue from non-brain tissue, has been challenging due to the ramification of the human brain structures and volatile parameters in the magnetic resonance imaging (MRI) procedures. It has been one of the most critical preprocessing steps in medical image analysis. We propose a hybrid skull stripping algorithm that is based on texture feature analysis, fuzzy possibilistic c-means (FPCM), and morphological operations. The input MR image is first processed to obtain two texture feature maps, to which the FPCM is applied for acquiring brain and non-brain masks. A number of morphological operations are subsequently performed to extract the brain. Our algorithm has been compared with two famous methods and evaluated on the internet brain segmentation repository (IBSR) datasets. Preliminary experimental results suggested that this new framework achieved high accuracy and outperformed the compared methods. We believe that the proposed scheme is of effectively potential in a wide variety of brain MR image segmentation applications.
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12:05-12:20, Paper FrBT14.6 | Add to My Program |
Segmentation of Hyper-Acute Cerebral Infarct Based on Random Forest and Sparse Coding from Diffusion Weighted Imaging |
Zhang, Xiaodong | Shenzhen Inst. of Advanced Tech. Chinese Acad. of S |
Elazab, Ahmed | Shenzhen Inst. of Advanced Tech |
Hu, Qingmao | Shenzhen Inst. of Advanced Tech. Chinese Acad. of S |
Keywords: Image segmentation, Image feature extraction, Brain image analysis
Abstract: Irreversible infarcts are critical for the assessment of potential risk and benefit pertaining to thrombolysis in hyper-acute ischemic stroke. It is a challenging work to segment infarct at hyper-acute stage due to the substantial variability. A general abnormal tissue segmentation method is proposed and applied to segment hyper-acute ischemic infarct in this paper. Multiple features are designed to train a random forest classifier for voxel classification. Sparse coding based bag-of-features is adopted to train a region classifier for infarct region recognition. The proposed method has been validated on 98 consecutive patients recruited within 6 hours from onset and achieved a higher Dice coefficient 0.774±0.117 than the other two existing methods (0.755±0.118; 0.597±0.204). It could provide a potential tool to quantify infarcts from diffusion weighted imaging at hyper-acute stage with accuracy to assist the decision making especially for thrombolytic therapy.
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FrBT15 Oral Session, Webster Room |
Add to My Program |
Point of Care Technologies |
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Chair: Penzel, Thomas | Charite Univ. Berlin |
Co-Chair: Panescu, Dorin | Advanced Cardiac Therapeutics |
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10:50-11:05, Paper FrBT15.1 | Add to My Program |
Development of a Gesture and Voice Controlled System for Burn Injury Prevention in Individuals with Disabilities |
Swanepoel, Liam | Stellenbosch Univ |
Van Den Heever, Dawie | Stellenbosch Univ |
Dellimore, Kiran | Philips Res |
Keywords: Point of care - Home-based applications, Point of care - Technologies in resource limited settings
Abstract: Burn injury is a major public health issue in developing countries, with most injuries being largely associated with the use of kitchen stoves. This study details the development of a cost-effective gesture and voice recognition controlled (GVC) system to be used by individuals with disabilities to reduce the likelihood of burn injury and improve their quality of life. The device replaces conventional dial controls with voice and hand gesture recognition sensors and software which are designed to be easily implemented into a household kitchen. Preliminary evaluation of the GVC system’s performance in gesture and voice recognition, gas leak detection and ignition control tests were conducted using a Bunsen burner as a stove top surrogate. The voice and gesture recognition tests yielded sensitivities of 88% and 100%, respectively. These results suggest that the GVC system may be a promising solution for burn injury prevention pending further work to improve its reliability and robustness.
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11:05-11:20, Paper FrBT15.2 | Add to My Program |
A Novel Mainstream Capnometer System for Endoscopy Delivering Oxygen |
Kabumoto, Kenichiro | Nihon Koden Corp |
Takatori, Fumihiko | Nihon Kohden Corp |
Inoue, Masayuki | Nihon Kohden Corp |
Keywords: Point of care - Respiratory monitoring, Point of care - Detection and monitoring, Medical technology - Design and development
Abstract: Capnometry is a method to measure carbon dioxide (CO2) in exhaled gas and it has been used in patients to monitor their respiratory status. Monitoring of exhaled CO2 during endoscopic procedures has been shown to be effective in detecting drug-induced respiratory depression. Oxygen (O2) supplementation is given to patients to abolish hypoxia during endoscopy. However, oxygen administration can interfere with CO2 measurement owing to oxygen flow. Therefore, we developed cap-ONE Biteblock for patients undergoing endoscopy with oxygen supply to measure CO2 accurately. In this study we evaluated the basic performance of cap-ONE Biteblock. The cap-ONE Biteblock system could accurately measure CO2 and efficiently supply O2 comparing to conventional devices via a bench study.
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11:20-11:35, Paper FrBT15.3 | Add to My Program |
A Novel Smartphone Camera-LED Communication for Clinical Signal Transmission in Mhealth-Rehabilitation System |
Pradana Rachim, Vega | Pukyong National Univ |
An, Jinyoung | Pukyong National Univ |
Pham, Ngoc Quan | Pukyong National Univ |
Chung, Wan-Young | Pukyong National Univ |
Keywords: Point of care - Home-based applications, Information communication and networking - mHealth innovations, Point of care - Heart rate monitoring
Abstract: In this paper, an implementation of mobile-Visible Light Communication (mVLC) technology for clinical data transmission in home-based mobile-health (mHealth) rehabilitation system is introduced. Mobile remote rehabilitation program is the solutions for improving the quality of care of the clinicians to the patients with chronic condition and disabilities. Typically, the program inquires routine exercises which obligate patients to wear wearable electronic sensors for hours in a specific range of time. Thus it motivate us to develop a novel harmless biomedical communicating system since most of the device's protocol was based on RF communication technology which risky for a human body in term of long term usage due to RF exposure and electromagnetic interference (EMI). The proposed system are designed to utilize a visible light as a medium for hazardless-communication between wearable sensors and a mobile interface device (smartphone). Multiple clinical data such as photoplethysmogram (PPG), electrocardiogram (ECG), and respiration signal are transmitted through LED and received by a smartphone camera. Furthermore, a smartphone also used for local interface and data analyzer henceforth sent the data to the cloud for further clinician’s supervision.
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11:35-11:50, Paper FrBT15.4 | Add to My Program |
Profiling a Multiplex Short Tandem Repeat Loci from Human Urine with Use of Low Cost On-Site Technology for Verification of Sample Authenticity |
Pires, Nuno M. M. | 1. Univ. Coll. of Southeast Norway; 2. Inst. of Appl |
Dong, Tao | Univ. Coll. of Southeast Norway - HSN, TekMar |
Berntzen, Lasse | Department of Business, History and Social Sciences, School of B |
Lønningdal, Torill | Innovatoriet at Department of Res. and Internationalisation, |
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11:50-12:05, Paper FrBT15.5 | Add to My Program |
Fall Detection Using Smart Floor Sensor and Supervised Learning |
Minvielle, Ludovic | ENS Cachan (Univ. Tarkett GDL SA (Company) |
ATIQ, Mounir | ENS Cachan ( Univ. ), Tarkett GDL SA ( Company ) |
Serra, Renan | Tarkett GDL SA |
Mougeot, Mathilde | Univ. Paris-Diderot |
Vayatis, Nicolas | Centre De Mathématiques Et Leurs Applications, ENS Cachan, CNRS, |
Keywords: Point of care - Detection and monitoring, Point of care - Home-based applications, Global healthcare challenges
Abstract: Falls are a major risk for elderly people’s health and independence. Fast and reliable fall detection can improve chances of surviving the accident and coping with its physical and psychological consequences. Recent research has come up with various solutions, all suffering from significant drawbacks, one of them being the intrusiveness into patient’s life. This paper proposes a novel fall detection system based on a sensitive floor sensor made out of a piezoelectric material and a machine learning approach. The detection is done by a combination between a supervised Random Forest and an aggregation of its output over time. The database was made using acquisitions from 28 volunteers simulating falls and other behaviours. Unlike existent fall detection systems, our solution offers the advantages of having a passive sensor (no power supply is needed) and being completely unobtrusive since the sensor comes with the floor. Results are compared with state-of-the-art classification algorithms. On our database, good performance of fall detection was obtained with a True Positive Rate of 94.4% and a False Positive Rate of 2.4%.
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12:05-12:20, Paper FrBT15.6 | Add to My Program |
Respiration and Heartbeat Monitoring Using a Distributed Pulsed MIMO Radar |
Walterscheid, Ingo | Fraunhofer FHR |
Smith, Graeme E. | The Ohio State Univ |
Keywords: Point of care - Respiratory monitoring, Point of care - Heart rate monitoring
Abstract: This paper addresses non-contact monitoring of physiological signals induced by respiration and heartbeat. To detect the tiny physiological movements of the chest or other parts of the torso, a Mulitple-Input Multiple-Output (MIMO) radar is used. The spatially distributed transmitters and receivers are able to detect the chest surface movements of one or multiple persons in a room. Due to several bistatic measurements at the same time a robust detection and measuring of the breathing and heartbeat rate is possible. Using an appropriate geometrical configuration of the sensors even a localization of the person is feasible.
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FrBT16 Minisymposium, Rushmer Room |
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Implementation of Information Technologies for Biomedical Engineering |
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Chair: Kim, Chulhong | Pohang Univ. of Science and Tech |
Co-Chair: Horio, Keiichi | Kyushu Inst. of Tech |
Organizer: Kim, Chulhong | Pohang Univ. of Science and Tech |
Organizer: Horio, Keiichi | Kyushu Inst. of Tech |
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10:50-11:05, Paper FrBT16.1 | Add to My Program |
Imparting Motor-Skills to Humanoid Robots Using Bayesian Nonparametric Latent Spaces (I) |
Koganti, Nishanth | Nara Inst. of Science and Tech |
Tamei, Tomoya | Nara Inst. of Science and Tech |
Ikeda, Kazushi | Nara Inst. of Science and Tech |
Shibata, Tomohiro | Kyushu Inst. of Tech |
Keywords: Image visualization
Abstract: Motor-skill learning for complex robotic tasks is challenging due to high task variability. In this study, we propose a user-friendly tool for Learning from Demonstration (LfD) that relies on the use of Bayesian nonparametric dimensionality reduction. We implement our framework in an assistive robotics setting for imparting motor-skills to a dual-arm robot performing clothing assistance tasks.
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11:05-11:20, Paper FrBT16.2 | Add to My Program |
Development of Axillary Pressure Feedback System for Crutch Walking (I) |
Wada, Chikamune | Kyushu Inst. of Tech |
nagasaki, takayuki | Kyushu Univ. of Nursing and Social Welfare |
Keywords: Image visualization
Abstract: This study aimed to decrease risk of falls via displacement of the axilla during crutch walking. We developed an axillary pressure feedback system that provided visual and/or auditory information to crutch users. Results suggested that this feedback system was effective in beginner crutch users.
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11:20-11:35, Paper FrBT16.3 | Add to My Program |
Ensemble Classification for Robustness Improvement in Image-Based Diagnosis Support Systems (I) |
Horio, Keiichi | Kyushu Inst. of Tech |
Keywords: Image classification, Image feature extraction
Abstract: In this paper, we introduce an ensemble classification method using local images for diagnosis support system based on intraoral images. In the developing system, dentists are required to manually cutout a local image including disease area from the intraoral image. This manual operation includes serious individual difference, and it causes decrease of accuracy. By applying a concept of ensemble method, influence of individual difference can be weakened.
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11:35-11:50, Paper FrBT16.4 | Add to My Program |
Ocular Vasculature Analysis Using Photoacoustic Microscopy and Random Sample Consensus Algorithm (I) |
Jeon, Seungwan | Pohang Univ. of Science and Tech |
Kim, Chulhong | Pohang Univ. of Science and Tech |
Keywords: Optical imaging
Abstract: Ocular vessels are an important indicator in ophthalmology, but it is difficult to observe them at a glance because the ocular blood vessels are very small and the structure is complex. In this study, we propose a new method of analyzing the ocular vasculature using photoacoustic micriscopy and random sample consensus algorithm. We found the eyeball surface and reconstructed an image that is easier to analze the ocular vasculature than the conventional visualization method.
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FrBT17 Oral Session, Einthoven Hall |
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Signal Processing - Electromyography |
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Chair: Kerkman, Jennifer N. | Vrije Univ. Amsterdam |
Co-Chair: Zhang, Yingchun | Univ. of Houston |
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10:50-11:05, Paper FrBT17.1 | Add to My Program |
Simulations of High-Density Surface Electromyograms in Dynamic Muscle Contractions |
Glaser, Vojko | Univ. of Maribor, Faculty of Electrical Engineeringand Comp |
Farina, Dario | Bernstein Center for Computational Neuroscience, Univ |
Holobar, Ales | Univ. of Maribor, Faculty of Electrical EngineeringandCompu |
Keywords: Signal pattern classification, Physiological systems modeling - Signal processing in simulation, Principal and independent component analysis - Blind source separation
Abstract: We describe the extension of pre-existing cylindrical volume conductor model to synthetic high-density surface electromyograms (hdEMG), simulated during dynamic contractions of fusiform skeletal muscles. Its modular structure comprises two main parts. First, dynamic changes of motor unit action potentials (MUAPs) during 36 discrete steps of muscle shortening are simulated. Second, the increase in depth of simulated motor units (MUs) due to shortening and thickening of muscle fibers is simulated. MU firing patterns are generated with the model proposed by Fuglevand et al. and convolved with simulated MUAPs. In this way, the hdEMG simulator can be used to generate dynamic hdEMG of arbitrary muscle shortening, thickening and excitation profiles. In order to demonstrate the value of the aforementioned simulator we independently analyze the impact of muscle shortening and muscle thickening on MU identification by Convolution Kernel Compensation (CKC) technique.
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11:05-11:20, Paper FrBT17.2 | Add to My Program |
Performance Evaluation of Noise-Assisted Multivariate Empirical Mode Decomposition and Its Application to Multichannel EMG Signals |
Zhang, Yi | Univ. of Electronic Science and Tech. of China |
Su, Steven Weidong | Univ. of Tech. Sydney |
Xu, Peng | Univ. of Electr Science and Tech. of China |
Yao, Dezhong | Univ. of Electronic Science and Tech. of China |
Keywords: Time-frequency and time-scale analysis - Empirical mode decomposition in biosignal analysis, Nonlinear dynamic analysis - Nonlinear filtering
Abstract: The use of the Empirical Mode Decomposition (EMD) for nonlinear signal processing has been popularized in the recent years. However, its utility for the processing of multichannel Electromyography (EMG) signals is still limited. This paper investigates the decomposition performance of multichannel EMGs by using EMD-based approaches, Ensemble EMD (EEMD), Multivariate EMD (MEMD), and Noise-Assisted MEMD (NA-MEMD). In the experiment, 11 male subjects undergo three exercise programs, leg extension from a sitting position, flexion of the leg up, and gait, while electrodes are placed on the muscle groups, biceps femoris, vastus medialis, rectus femoris, and semitendinosus. The outcomes are then quantitatively estimated on the basis of three criterions, the number of Intrinsic Mode Functions (IMFs), mode-alignment and mode-mixing. Results show both MEMD and NA-MEMD can guarantee equal numbers of IMFs, whereas for mode-alignment and mode-mixing, NA-MEMD is optimal compared with MEMD and EEMD, and MEMD is merely better than EEMD. This finding implies that NA-MEMD is effective for simultaneously analyzing IMFs based frequency bands. It has a vital clinical implication in exploring the neuromuscular patterns that enable the multiple muscle groups to coordinate while performing functional activities of daily living.
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11:20-11:35, Paper FrBT17.3 | Add to My Program |
Measuring the Interactions between Different Locations in a Muscle to Monitor Localized Muscle Fatigue |
Bingham, Adrian | RMIT Univ. Melbourne |
Poosapadi Arjunan, Sridhar | RMIT Univ |
Kant Kumar, Dinesh | RMIT Univ |
Keywords: Physiological systems modeling - Signal processing in physiological systems, Nonlinear dynamic analysis - Biomedical signals, Physiological systems modeling - Signals and systems
Abstract: In this study we investigated a technique for estimating the progression of localized muscle fatigue. This technique measures the dependence between motor units using high density surface electromyogram (HD-sEMG) and is based on the Normalized Mutual Information (NMI) measure. The NMI between every pair combination of the electrode array is computed to measure the interactions between electrodes. Participants in the experiment had an array of 64 electrodes (16 by 4) placed over the TA of their dominate leg such that the columns of the array ran parallel with the muscle fibers. The HD-sEMG was recorded whilst the participants maintained an isometric dorsiflexion with their dominate foot until task failure at 40% and 80% of their maximum voluntary contraction (MVC). The interactions between different locations over the muscle were computed using the recorded HD-sEMG signals. The results show that the average interactions between various locations over the TA significantly increased during fatigue at both levels of contraction. This can be attributed to the dependence in the motor units.
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11:35-11:50, Paper FrBT17.4 | Add to My Program |
Analysis of One Repetition During Biceps Curl Exercise among Age-Matched Adult Volunteers Using Endurance, Curl Speed and Surface Electromyography Signals |
Marri, Kiran | Indian Inst. of Tech. Madras, Chennai |
Maitra, Diptasree | IIT Madras |
Ramakrishnan, Swaminathan | IIT Madras, India |
Keywords: Nonlinear dynamic analysis - Biomedical signals, Connectivity measurements, Data mining and processing in biosignals
Abstract: Exercises under isometric and dynamic contractions are influenced by the rate coding and recruitment strategies. The study of muscle strength under dynamic contraction is normally performed using one-repetition maximum (1-RM) method. There are several variants of deriving one repetition method using number of repetitions and load that are useful in physical fitness and clinical rehabilitation program. However, the factors of dynamic contractions such as endurance time, speed of muscle contractions and muscle activity are not considered in 1-RM methods. The muscular activities are analyzed using surface electromyography (sEMG) signals. Limited work has been reported on the relationship between the 1-RM method and factors such as endurance time, speed of contraction and sEMG activity. In this work, a modified 1-RM method is proposed, namely, N-RM, using load, number of repetitions, endurance time, speed of contraction and normalized sEMG activity. For this purpose, sEMG signals are recorded from 58 healthy subjects under standard dynamic contraction protocol involving curl exercise. Conventional 1-RM is computed by using Epley’s method and compared with proposed method using correlation analysis. The results show that 1-RM increases linearly with number of curls (r=1) but has a poor correlation coefficient with sEMG (r=0.01) and endurance time (r =0.4). The curl speed for lower 1-RM and higher 1-RM did not show any statistical difference (p =0.2). The proposed N-RM is observed to have good correlation with endurance time (r=0.734), curl speed (r=0.893) and sEMG activity (r=0.8851). These results demonstrate that the proposed N-RM is highly correlated to factors influencing the dynamic contractions. This method can be further extended to assess muscles under various clinical disorders and sports training.
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11:50-12:05, Paper FrBT17.5 | Add to My Program |
Antagonist Thigh-Muscle Activity in 6-To-8-Year-Old Children Assessed by Surface EMG During Walking |
Di Nardo, Francesco | Pol. Univ. of Marche |
Strazza, Annachiara | Univ. Pol. Delle Marche |
Mengarelli, Alessandro | Univ. Pol. Delle Marche |
Ercolani, Serena | Univ. Pol. Delle Marche |
Burattini, Laura | Univ. Pol. Delle Marche |
Fioretti, Sandro | Univ. Pol. Delle Marche |
Keywords: Physiological systems modeling - Signal processing in physiological systems
Abstract: Analysis of muscle co-contractions seems to be relevant in the characterization of children pathologies such as spastic cerebral palsy. The aim of the study was the quantification of thigh-muscle co-contractions during walking in healthy children. To this aim, the Statistical Gait Analysis, a recent methodology providing a statistical characterization of gait, was performed on surface EMG signals from Vastus Medialis (VM) and Lateral Hamstrings (LH) in 30 healthy 6-to-8-year-old children. Muscular co-contraction was assessed as the overlapping period between activation intervals of agonist and antagonist muscles. As in adults, VM activity occurring from terminal swing to the following loading response superimposed LH activity in the same percentage of the gait cycle. This co-contraction occurred in order to control knee joint stability during weight acceptance. It was acknowledged in the totality (100 %) of the considered strides. Concomitant activity of VM and LH was detected also in the second half of stance phase in 17.1 ± 4.8 % of the considered strides. Working VM and LH on different joints, this concomitant activity of antagonist muscles should not be considered as an actual co-contraction. Present findings provide new information on the variability of the reciprocal role of VM and LH during child walking, useful for comparison between normal and pathological walking in the clinical context and for designing future studies on maturation of gait.
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12:05-12:20, Paper FrBT17.6 | Add to My Program |
Evaluation of a Laser-Based Sensor for the Diagnosis of Neurological Disorders |
Tenner, Felix | Lehrstuhl Für Photonische Tech |
Regensburger, Martin | Clinic of Neurology, Friedrich-Alexander-Univ. Erlangen-Nü |
Schramm, Axel | Univ. Hospital Erlangen |
Söhle, Mona | Inst. of Photonic Tech. Friedrich-Alexander-Univ |
Schwarzkopf, Karen | Inst. of Photonic Tech. Friedrich-Alexander-Univ |
Zalevsky, Zeev | Nano Photonics Center at the Inst. of Nanotechnology and Adv |
Schmidt, Michael | Inst. of Photonic Tech. Friedrich-Alexander-Univ |
Keywords: Diagnostic devices - Physiological monitoring, Clinical engineering, Ambulatory Diagnostic devices - Point of care technologies
Abstract: Involuntary muscle activities like fasciculations or tremor are an indication for several neurological disorders. However, currently used techniques for measuring those activities are limited due to their invasiveness, the unsuitability for measuring a whole body simultaneously and the lack of an objective measurement of amplitude and duration of muscle activity. Hence, we developed a new laser-based sensor for the remote quantification of muscle activity. In the present paper we show a basic evaluation of our system by reference to ultrasound measurements. Our results show the detection limits of our remote sensor technology in terms of fasciculation size and depth within the muscle. Those results will help us for a better interpretation of our measurement results and hold promise for the future development of our system.
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FrBT18 Oral Session, Montgomery Hall |
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Nonlinear Dynamic Analysis II - Cardiovascular Signals |
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Chair: Castiglioni, Paolo | Fondazione Don Carlo Gnocchi ONLUS |
Co-Chair: Lee, Jong-Ha | Keimyung Univ. School of Medicine |
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10:50-11:05, Paper FrBT18.1 | Add to My Program |
Characterization of Doctor-Patient Communication Using Heartbeat Nonlinear Dynamics: A Preliminary Study Using Lagged Poincaré Plots |
Nardelli, Mimma | Univ. of Pisa |
Del Piccolo, Lidia | Univ. of Verona |
Danzi, Olivia Purnima | Univ. of Verona |
Perlini, Cinzia | Univ. of Verona, Verona |
Tedeschi, Federico | Univ. of Verona |
Greco, Alberto | Univ. of Pisa |
Scilingo, Enzo Pasquale | Univ. of Pisa |
Valenza, Gaetano | Univ. of Pisa |
Keywords: Nonlinear dynamic analysis - Biomedical signals, Physiological systems modeling - Signal processing in physiological systems, Signal pattern classification
Abstract: Emphatic doctor-patient communication has been associated with an improved psycho-physiological well-being involving cardiovascular and neuroendocrine responses. Nevertheless, a comprehensive assessment of heartbeat linear and nonlinear/complex dynamics throughout the communication of a life-threatening disease has not been performed yet. To this extent, we here study heart rate variability (HRV) series gathered from 17 subjects while watching a video where an oncologist discloses the diagnosis of a cancer metastasis to a patient. Further 17 subjects watched the same video including additional affective emphatic contents. For the assessment of the two groups, linear heartbeat dynamics was quantified through measures defined in the time and frequency domains, whereas nonlinear/complex dynamics referred to measures of entropy, and combined Lagged Poincare Plots (LPP) and symbolic analyses. Considering differences between the beginning and the end of the video, results from non-parametric statistical tests demonstrated that the group watching emphatic contents showed HRV changes in the LF/HF ratio exclusively. Conversely, the group watching the purely informative video showed changes in vagal activity (i.e., HF power), LF/HF ratio, as well as LPP measures. Additionally, a Support Vector Machine algorithm including HRV nonlinear/complex information was able to automatically discern between groups with an accuracy of 76.47%. We therefore propose the use of heartbeat nonlinear/ complex dynamics to objectively assess the empathy level of healthy women.
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11:05-11:20, Paper FrBT18.2 | Add to My Program |
Multifractal Multiscale DFA of Cardiovascular Time Series: Differences in Complex Dynamics of Systolic Blood Pressure, Diastolic Blood Pressure and Heart Rate |
Castiglioni, Paolo | Fondazione Don Carlo Gnocchi ONLUS |
Lazzeroni, Davide | Fondazione Don Carlo Gnocchi, Parma, Italy |
Brambilla, Valerio | Fondazione Don Carlo Gnocchi, Parma, Italy |
Coruzzi, Paolo | Department of Clinical and Experimental Medicine, Univ. Of |
Faini, Andrea | Istituto Auxologico Italiano |
Keywords: Nonlinear dynamic analysis - Biomedical signals, Physiological systems modeling - Signal processing in physiological systems, Time-frequency and time-scale analysis - Nonstationary processing
Abstract: The heart-rate fractal dynamics can be assessed by Detrended Fluctuation Analysis (DFA), originally proposed for estimating a short-term coefficient, alpha1 (for scales n≤12 beats), and a long-term coefficient alpha2 (for longer scales). Successively, DFA was extended to provide a multiscale alpha, i.e. a continuous function of n, alpha(n); or a multifractal alpha, i.e. a function of the order q of the fluctuations moment, alpha(q). Very recently, a multifractal-multiscale DFA was proposed for evaluating multifractality at different scales separately. Aim of this work is to describe the multifractal multiscale dynamics of three cardiovascular signals often recorded beat by beat in physiological and clinical settings: systolic blood pressure (SBP), diastolic blood pressure (DBP) and pulse interval (PI, inverse of the heart rate). We recorded SBP, DBP and PI for at least 90’ in 65 healthy volunteers at rest, and adapted the previously proposed multifractal multiscale DFA to estimate alpha as function of the temporal scale, tau, between 15 and 450 s, and of the order q, between -5 and 5. We report, for the first time: 1) substantial differences among alpha(q,tau) surfaces of PI, SBP and DBP; 2) a strong dependency of the degree of multifractality on the temporal scale.
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11:20-11:35, Paper FrBT18.3 | Add to My Program |
Cardiovascular and Respiratory Variability During Orthostatic and Mental Stress: A Comparison of Entropy Estimators |
Valente, Martina | Univ. of Trento |
Javorka, Michal | Comenius Univ. Jessenius Faculty of Medicine |
Turianikova, Zuzana | Department of Physiology, Comenius Univ. Jessenius Faculty |
Czippelova, Barbora | Department of Physiology, Comenius Univ. Jessenius Faculty |
Krohova, Jana | Comenius Univ. in Bratislava |
Nollo, Giandomenico | Univ. of Trento |
Faes, Luca | Univ. of Trento |
Keywords: Physiological systems modeling - Signal processing in physiological systems, Nonlinear dynamic analysis - Biomedical signals, Physiological systems modeling - Multivariate signal processing
Abstract: The aim of this study is to characterize cardiovascular and respiratory signals during orthostatic and mental stress as reflected in indices of entropy and complexity, providing a comparison between the performance of different estimators. To this end, the heart rate variability, systolic blood pressure, diastolic blood pressure and respiration time series were extracted from the recordings of 61 healthy volunteers undergoing a protocol consisting of supine rest, head-up tilt test and mental arithmetic task. The analysis was performed in the information domain using measures of entropy and conditional entropy, estimated through model-based (linear) and model-free (binning, nearest neighbor) approaches. Our results show that different types of stress elicited different responses in the employed indices. On one hand, entropy mainly reflected known changes in the variance of physiological time series. On the other hand, the information conveyed by conditional entropy allowed to characterize the complexity of the four time series during the two stress tasks: we found that cardiac and vascular dynamics underwent a reduction in complexity as a consequence of postural stress, while vascular and respiratory complexity increased as a result of mental stress. As for the performance of different estimators, we did not find substantial differences between model-based and model-free approaches, possibly indicating that significant non-linear dynamics did not appear in the studied conditions.
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11:35-11:50, Paper FrBT18.4 | Add to My Program |
Secondary Measures of Regularity from an Entropy Profile in Detecting Arrhythmia |
Udhayakumar, Radhagayathri | Univ. of Melbourne |
Karmakar, Chandan | Deakin Univ |
Palaniswami, Marimuthu | The Univ. of Melbourne |
Keywords: Nonlinear dynamic analysis - Biomedical signals, Signal pattern classification
Abstract: The most recently introduced concept of a ‘complete entropy profile’ is a non-parametric (with regard to tolerance r) approach of entropy estimation. Given a signal, on generating its complete entropy profile, numerous secondary measures of regularity can be derived from the same. These profile based measures are seen to outperform the traditional ApEn statistic (evaluated at a single r) in estimating signal regularity. In this paper, we compare the performance of ApEn (evaluated at an r=0.15*SD of signal and an m=2) with that of profile based measures such as MaxApEn, TotalApEn, AvgApEn, SDApEn, kurtApEn and skewApEn, in detecting ‘Arrhythmic’ RR interval signals from ‘Normal’ RR interval signals. Results indisputably prove the superiority of AvgApEn (AUC>0.9 at data lengths Ngeq200) and MaxApEn (AUC>0.75 at all data lengths) as regularity statistics in detecting Arrhythmia, above all the other measures used.
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11:50-12:05, Paper FrBT18.5 | Add to My Program |
Multivariate Symbolic Dynamics for Analysis of Respiratory-Cardiovascular Interactions |
Reulecke, Sina | Univ. Autónoma Metropolitana |
Charleston-Villalobos, Sonia | Univ. Autonoma Metropolitana |
Voss, Andreas | Univ. of Applied Sciences Jena |
Gonzalez-Camarena, Ramon | Univ. Autonoma Metropolitana |
Gaitan-Gonzalez, Mercedes | Univ. Autonoma Metropolitana |
Gonzalez-Hermosillo, Jesus Antonio | Inst. Nacional De Cardiología |
HERNANDEZ-PACHECO, GUADALUPE | Inst. NACIONAL DE CARDIOLOGIA "IGNACIO CHAVEZ" |
Aljama-Corrales, Tomas | Univ. Autonoma Metropolitana |
Keywords: Nonlinear dynamic analysis - Biomedical signals, Physiological systems modeling - Multivariate signal processing, Physiological systems modeling - Signal processing in physiological systems
Abstract: Abstract— In this work, a nonlinear method to study multivariate interactions, called multivariate symbolic dynamics (MSD), was introduced. The usefulness of this technique was studied on respiratory-cardiovascular data from young women with vasovagal syncope (VVS) and from healthy subjects. The study included 16 female patients diagnosed with VVS and 24 age-matched healthy subjects (12 women). All subjects were enrolled in a head-up tilt (HUT) test, breathing normally, including 5 min of supine position and 18 to 28 min of 70° orthostatic phase. The MSD parameters were dynamically obtained for 5-min windows shifted by 1 min during HUT test. In supine position there were no considerable differences. During orthostatic phase, parameters from MSD showed a highly significantly (p=0.00005) increased occurrence of impaired respiratory-cardiovascular interactions in female patients susceptible to vasovagal syncope. This study provided promising results for a new multivariate method to investigate respiratory-cardiovascular interactions.
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12:05-12:20, Paper FrBT18.6 | Add to My Program |
Nonlinear Dynamic Analysis of the Cardiorespiratory System in Patients Undergoing the Weaning Process |
Arizmendi, Carlos | Univ. Autonoma De Bucaramanga |
Trapero, Jose Ignacio | Univ. Autonoma De Bucaramanga |
Gonzalez Acevedo, Hernando | Univ. Autónoma De Bucaramanga |
Forero, Carlos Adolfo | Univ. Autonoma De Bucaramanga |
Giraldo, Beatriz | Univ. Poiltècnica De Catalunya |
Keywords: Nonlinear dynamic analysis - Biomedical signals, Signal pattern classification, Neural networks and support vector machines in biosignal processing and classification
Abstract: In this work, the cardiorespiratory pattern of patients undergoing extubation process is studied. First, the respiratory and cardiac signals were resampled, next the Symbolic Dynamics (SD) technique was implemented, followed of a dimensionality reduction applying Forward Selection (FS) and Moving Window with Variance Analysis (MWVA) methods. Finally, the Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM) classifiers were used. The study analyzed 153 patients undergoing weaning process, classified into 3 groups: Successful Group (SG: 94 patients), Failed Group (FG: 39 patients), and patients who had been successful during the extubation and had to be reintubated before 48 hours, Reintubated Group (RG: 21 patients). According to the results, the best classification present an accuracy higher than 88.98 ± 0.013% in all proposed combinations.
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FrCT1 Oral Session, Roentgen Hall |
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Signal Pattern Classification - Cardiovascular Signals I |
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Chair: Wu, Shun Chi | National Tsing Hua Univ |
Co-Chair: Kim, Kiwoong | Korea Res. Inst. of Standards and Science |
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14:20-14:35, Paper FrCT1.1 | Add to My Program |
A Cancelable Biometric Scheme Based on Multi-Lead ECGs |
Chen, Peng-Tzu | National Tsing Hua Univ |
Wu, Shun Chi | National Tsing Hua Univ |
Hsieh, Jui Hsuan | National Tsing Hua Univ |
Keywords: Signal pattern classification, Data mining and processing in biosignals, Physiological systems modeling - Multivariate signal processing
Abstract: Biometric technologies offer great advantages over other recognition methods, but there are concerns that they may compromise the privacy of individuals. In this paper, an electrocardiogram (ECG)-based cancelable biometric scheme is proposed to relieve such concerns. In this scheme, distinct biometric templates for a given beat bundle are constructed via "subspace collapsing." To determine the identity of any unknown beat bundle, the multiple signal classification (MUSIC) algorithm, incorporating a "suppression and poll" strategy, is adopted. Unlike the existing cancelable biometric schemes, knowledge of the distortion transform is not required for recognition. Experiments with real ECGs from 285 subjects are presented to illustrate the efficacy of the proposed scheme. The best recognition rate of 97.58 % was achieved under the test condition Ntrain = 10 and Ntest = 10.
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14:35-14:50, Paper FrCT1.2 | Add to My Program |
Adaptive Fourier Decomposition Based R-Peak Detection for Noisy ECG Signals |
Wang, Ze | Faculty of Science and Tech. Univ. of Macau |
Wong, Chi Man | Univ. of Macau |
Wan, Feng | Univ. of Macau |
Keywords: Data mining and processing in biosignals, Independent component analysis
Abstract: An adaptive Fourier decomposition (AFD) based R-peak detection method is proposed for noisy ECG signals. Although lots of QRS detection methods have been proposed in literature, most detection methods require high signal quality. The proposed method extracts the R waves from the energy domain using the AFD and determines the R-peak locations based on the key decomposition parameters, achieving the denoising and the R-peak detection at the same time. Validated by clinical ECG signals in the MIT-BIH Arrhythmia Database, the proposed method shows better performance than the Pan-Tompkin (PT) algorithm in both situations of a native PT and the PT with a denoising process.
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14:50-15:05, Paper FrCT1.3 | Add to My Program |
A Robust Automatic Mechanism for Electrocardiogram Interpretation in Telehealthcare |
Ho, Te-Wei | National Taiwan Univ |
Lai, Feipei | National Taiwan Univ |
Keywords: Data mining and processing - Pattern recognition, Data mining and processing in biosignals, Signal pattern classification
Abstract: Telehealthcare has become increasingly popular in clinical practice as a means of providing ubiquitous healthcare through long-term informative interactions and health monitoring. We have delivered a synchronized telehealthcare program since 2009. We have implemented a web-based clinical decision support system with a knowledge-based electrocardiogram (ECG) recognition mechanism as an augmentation service to assist medical practitioners doing decision making in clinical practice. To evaluate the capability and usage limits of this automatic ECG interpretation, the aim of this study was to validate the stability and robustness of proposed mechanism using stress testing through six simulation scenarios. According to experimental results, both of the processing items and processing time augmented steadily by the resource of hardware. Besides, under the cross-validation using 327,058 ECG signals from our telehealthcare program, the recognition classifiers yielded 86.8% accuracy in sinus detection and 88.4% accuracy in atrial fibrillation detection. In the future, this prominent mechanism of automatic ECG interpretation could widely offer high accessibility in the field of medical service. The findings of the present study also encourage and augment further support to implementation of screening and monitoring as part of telehealthcare.
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15:05-15:20, Paper FrCT1.4 | Add to My Program |
Designing ECG-Based Physical Unclonable Function for Security of Wearable Devices |
Yin, Shihui | Arizona State Univ |
Bae, ChiSung | Samsung Advanced Inst. of Tech |
Kim, Sang Joon | Samsung Electronics |
Seo, Jae-sun | Arizona State Univ |
Keywords: Signal pattern classification, Neural networks and support vector machines in biosignal processing and classification, Physiological systems modeling - Signal processing in simulation
Abstract: As a plethora of wearable devices are being introduced, significant concerns exist on the privacy and security of personal data stored on these devices. Expanding on recent works of using electrocardiogram (ECG) as a modality for biometric authentication, in this work, we investigate the possibility of using personal ECG signals as the individually unique source for physical unclonable function (PUF), which eventually can be used as the key for encryption and decryption engines. New signal processing and machine learning algorithms are developed that can learn and extract maximally different ECG features for different individuals and minimally different ECG features for the same individual over time. Experimental results show that the distribution of the intra-subject Hamming distance of extracted ECG features for the same person over time and the distribution of the inter-subject Hamming distance has minimal negligible overlap.
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15:20-15:35, Paper FrCT1.5 | Add to My Program |
A Body Position Influence on ECG Derived Respiration |
Przystup, Piotr | Gdansk Univ. of Tech |
Polinski, Artur | Gdansk Univ. of Tech |
Wtorek, Jerzy | Gdansk Univ. of Tech |
Bujnowski, Adam | Gdansk Univ. of Tech |
Kocejko, Tomasz | Gdansk Univ. of Tech |
Keywords: Data mining and processing in biosignals
Abstract: An influence of a human body position on an ECG derived respiration (EDR) signal is presented in the paper. Examinations were performed during deep, suspended and normal breathing for eight people in four different body positions. EDR and thoracic impedance signals were compared using correlation and standard deviation coefficients. Obtained results have shown that it is possible to monitor breath activity of people being in different position, however a precise interpretation of the signal obtained is limited.
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15:35-15:50, Paper FrCT1.6 | Add to My Program |
Analysis of PAM Clustering Accuracy for Cardiac Signals Classification |
kianimajd, Adell | Univ. of Algarve |
Ruano, M. Graça | FCT, Univ. of Algarve & CISUC-Univ. of Coimbra |
de Carvalho, Paulo | Univ. of Coimbra - NIF: 501617582 |
Henriques, Jorge | Univ. of Coimbra - NIF 501617582 |
Rocha, Teresa | Inst. Superior De Eng De Coimbra |
Ruano, Antonio | Univ. of Algarve |
Keywords: Data mining and processing - Pattern recognition
Abstract: Development of personalized health management systems involves automatic identification of the current data as normal or pathological; considering bio signals as time–series, the illness identification may be performed by seeking similarity between the current patient’s time-series data and a reference signal and then proceeding to illness stratification (clustering). Clustering performance depends on similarity measurement accuracy. We performed a study to evaluate how sensitive similarity methods are to small signal variations and how different cardiovascular diseases as well as length of data affect the subsequent clustering performance. Experiments were performed with electrocardiogram and arterial blood pressure signals of healthy subjects and patients with 4 types of pathologies. Results demonstrate that PAM clustering accuracy when Discrete Wavelet Transform (DWT) is considered achieved better values (76 to 84 % accuracy) than other works and that DWT is more sensitive to variations both in clusters’ classes and time series lengths than Pearson Correlation Coefficient.
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FrCT2 Invited Session, Cho Room |
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Recent Advances in Ultrasound Medical Imaging |
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Chair: Managuli, Ravi | Hitachi Aloka Medical America, Inc |
Co-Chair: Kim, Hyung Ham | Pohang Univ. of Science and Tech |
Organizer: Yoo, Yangmo | Sogang Univ |
Organizer: Kim, Hyung Ham | Pohang Univ. of Science and Tech |
Organizer: Managuli, Ravi | Hitachi Aloka Medical America, Inc |
Organizer: Chang, Jin Ho | Sogang Univ |
Organizer: Yoon, Changhan | Inje Univ |
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14:20-14:35, Paper FrCT2.1 | Add to My Program |
Ultrasound and Photoacoustic Multimodality Imaging Using Laser-Activated Perfluorocarbon Nanodroplets (I) |
Yoon, Changhan | Inje Univ |
Keywords: Ultrasound imaging - Other organs, Ultrasound imaging - Breast
Abstract: Laser-activated perfluorocarbon nanodroplets (PFCnDs) have been shown great promise in imaging and image-guided therapy. The liquid PFCnDs undergo a phase transition by pulsed laser irritation and convert to gas-core microbubbles. The activated PFCnDs produce strong photoacoustic (PA) signal through vaporization and resulting gas-core microbubbles provide a high echogenicity. This paper will provide recent progress of PFCnDs, especially focusing on imaging methods of PFCnDs.
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14:35-14:50, Paper FrCT2.2 | Add to My Program |
Advances in Ultrasound Imaging: Multi-Modality Fusion Imaging (I) |
Managuli, Ravi | Hitachi Aloka Medical America, Inc |
Keywords: Ultrasound imaging - Interventional, Ultrasound imaging - Breast, X-ray CT imaging
Abstract: Ultrasound fusion is a new technique available on recent commercial ultrasound systems. This technique involves the display of registered real-time Ultrasound images with a reference images acquired from other modalities such as CT/MRI. The fused images provide real-time anatomical ultrasound images with snapshots of anatomy and physiology provided on other non-real-time modalities. In another variant of fusion, the images acquired from US are registered with the previously acquired US images for temporal comparison. Fusion is in use for multitude of clinical applications, e.g., targeted prostate biopsy, breast conservative surgery, liver RF ablation monitoring, real-time image-guided biopsy, and follow-up studies to monitor growth of suspicious lesion. Many types of image registration techniques, magnetic-based, optical-based, robotic-based and image-based are employed for fusion imaging. In this presentation, we will cover details of fusion technique including clinical applications. We will also outline limitations and future challenges of
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14:50-15:05, Paper FrCT2.3 | Add to My Program |
Ultrasound-Assisted Photothermal Therapy (I) |
Chang, Jin Ho | Sogang Univ |
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15:05-15:20, Paper FrCT2.4 | Add to My Program |
A New Three-Dimensional Automated Breast Ultrasound Imaging System for Women with Dense Breast (I) |
Yoo, Yangmo | Sogang Univ |
Keywords: Ultrasound imaging - Breast, Image enhancement
Abstract: In this paper, an upright three-dimensional automated breast ultrasound (ABUS) imaging system is presented. In the upright ABUS imaging system, after the breast is fixed similar to X-ray mammography with much less pressure, a plurality of wide ultrasonic probes move with the fixed plate and scan to acquire three-dimensional images. Therefore, it can improve the scanning time as well as directly compare the acquired images with those from X-ray mammography. Moreover, an intelligent optimization technique that analyzes the patient data in real time and improves the image quality automatically when the breast is scanned is also developed. Furthermore, the computer assisted detection system is used to automatically detect breast masses and analyze the location shape, and boundary evaluation of detected breast masses to provide breast cancer risk information
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15:20-15:35, Paper FrCT2.5 | Add to My Program |
Array Transducers for High Definition Ultrasound Imaging (I) |
Kim, Hyung Ham | Pohang Univ. of Science and Tech |
Keywords: Ultrasound imaging - High-frequency technology, Retinal imaging, Ultrasound imaging - Interventional
Abstract: High frequency (15 – 50 MHz) ultrasound is widely used in preclinical imaging. Convex or phased array transducers may translate acoustic beams electronically, change the focal points with transmit beamforming and provide a wide field of view by a curved aperture or steered beams. High definition ultrasound imaging with convex or phased arrays is being explored to expand its applications not only in preclinical imaging but also in clinical imaging.
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FrCT3 Oral Session, Park Room |
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Innovative MRI Method |
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Chair: Zhao, Bo | MGH/HST Athinoula Martinos Center for Biomedical Imaging, Harvard Medical School |
Co-Chair: Chan, Kevin C. | New York Univ |
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14:20-14:35, Paper FrCT3.1 | Add to My Program |
White Matter Integrity Correlates with Choline Level in Dorsal Anterior Cingulate Cortex of Obsessive Compulsive Disorder Patients: A Combined DTI-MRS Study |
Wang, Ruilin | Shanghai Jiao Tong Univ |
Fan, Qing | Shanghai Mental Health Center, Shanghai Jiao Tong Univ. Sch |
Zhang, Zongfeng | Shanghai Mental Health Center, Shanghai Jiao Tong Univ. Sch |
Chen, Yongjun | Shanghai Mental Health Center, Shanghai Jiao Tong Univ. Sch |
Tong, Shanbao | Shanghai Jiao Tong Univ |
Li, Yao | Shanghai Jiao Tong Univ |
Keywords: Magnetic resonance imaging - Diffusion tensor and diffusion spectrum imaging, Magnetic resonance imaging - MR spectroscopy, Magnetic resonance imaging - MR neuroimaging
Abstract: Structural and functional neuroimaging studies have indicated that the cortico-striato -thalamo-cortical (CSTC) circuit contributes to the pathophysiology of obsessive compulsive disorder (OCD). As an essential component of CSTC circuit, the dorsal anterior cingulate cortex (dACC) plays an important role for its advanced function in cognition and emotion control. A comprehensive understanding of the dACC disruption in OCD pathological mechanism is desired. In this study, we performed a combined diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS) study in 15 OCD patients and 15 healthy controls to investigate the association between structural abnormality and metabolic alterations within the dACC area. We found a positive correlation between the dACC fractional anisotropy (FA) value and choline concentration in patients. Moreover, the FA was positively associated with OCD clinical symptom, especially the compulsive behavior, which showed the clinical relevance of dACC white matter integrity in OCD. To our knowledge, the present work is the first combined DTI-MRS study of OCD. Our findings demonstrated the co-occurrence of structural and metabolic changes within dACC in OCD patients. It was suggested that the disrupted white matter integrity might be accompanied with degraded cellular membrane turnover.
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14:35-14:50, Paper FrCT3.2 | Add to My Program |
A 3D Model-Based Simulation of Demyelination to Understand Its Effects on Diffusion Tensor Imaging |
Salan, Teddy | Univ. of Memphis |
Jacobs, Eddie | Univ. of Memphis |
Reddick, Wilburn | St. Jude Children's Res. Hospital |
Keywords: Magnetic resonance imaging - Diffusion tensor and diffusion spectrum imaging
Abstract: Demyelination is the progressive damage to the myelin sheath, a protective covering that surrounds a nerve's axon. Due to its high sensitivity to microscopic tissue changes, diffusion tensor imaging (DTI) is a powerful means of detecting signs of demyelination and axonal injury. In this paper, we present a 3D virtual model capable of simulating the complex Brownian motion of water molecules in a bundle of myelinated axons and glial cells for the purpose of synthesizing DTI data, characterizing and verifying the impact of demyelination on DTI. Our model consists of a highly detailed and realistic 3D representation of biological fiber bundles, with a myelin sheath covering the axons and glial cells in between them. The system simulates the Brownian motion of molecules to extract diffusion data. We perform our experiment for progressive stages of demyelination and demonstrate its effect on DTI measurements.
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14:50-15:05, Paper FrCT3.3 | Add to My Program |
Multi-View Collaborative Segmentation for Prostate MRI Images |
Wang, Xiu Ying | The Univ. of Sydney |
Tang, Wensi | Univ. of Sydney |
Cui, Hui | The Univ. of Sydney |
Zeng, Shan | Wuhan Pol. Univ |
Feng, Dagan | The Univ. of Sydney |
Fulham, Michael | Royal Prince Alfred Hospital |
Keywords: Magnetic resonance imaging - Other organs, Image segmentation
Abstract: Prostate delineation from MRI images is a prolonged challenging issue partially due to appearance variations across patients and disease progression. To address these challenges, our proposed collaborative method takes into account the computed multiple label-relevance maps as multiple views for learning the optimal boundary delineation. In our method, we firstly extracted multiple label-relevance maps to represent the affinities between each unlabeled pixel to the pre-defined labels to avoid the selection of handcrafted features. Then these maps were incorporated in a collaborative clustering to learn the adaptive weights for an optimal segmentation which overcomes the the seeds selection sensitivity problems. The segmentation results were evaluated over 22 prostate MRI patient studies with respect to dice similarity coefficient (DSC), absolute relative volume difference (ARVD) and average symmetric surface distance (ASSD) (mm). The results and t-Test demonstrated that the proposed method improved the segmentation accuracy and robustness and the improvement was statistically significant.
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15:05-15:20, Paper FrCT3.4 | Add to My Program |
A Portable, Low-Cost, 3D-Printed Main Magnetic Field System for Magnetic Imaging |
Kang, Iksung | Seoul National Univ |
Keywords: Magnetic resonance imaging - MR spectroscopy
Abstract: In this paper, a portable, low-cost, 3D-printed system for main magnetic field is proposed to suggest a solution for accessibility problems of current magnetic imaging systems, e.g. MRI scanner, their size and cost. The system consists of twelve pairs of NdFeB N35 permanent magnets arranged in a Halbach array in a 3D-printed, cylindrical container based on FEM simulation results by COMSOL Multiphysics 4.4b. Its magnetic field homogeneity and field strength were measured by Hall sensors, WSH-135 XPAN2 by Wilson Semiconductor, and the container was printed by 3DISON H700 by Rokit. The system generated a 5-mm imaging quality FOV and main magnetic field of 120 mT with a 12 % error in the field strength. Also, a hundred dollar was enough for the manufacture of the system with a radius of 6 cm and height of 10 cm. Given the results, I believe the system will be useful for some magnetic imaging applications, e.g. EPRI and low-field MRI.
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15:20-15:35, Paper FrCT3.5 | Add to My Program |
Accelerated Magnetic Resonance Spectroscopy with Vandermonde Factorization |
Qu, Xiaobo | Xaimen Univ |
Ying, Jiaxi | Department of Electronic Science, Xiamen Univ |
Cai, Jian-Feng | Department of Mathematics, Hong Kong Univ. of Science and T |
Chen, Zhong | Xiamen Univ |
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15:35-15:50, Paper FrCT3.6 | Add to My Program |
A Novel 3D-Printed Mechanical Actuator Using Centrifugal Force for Magnetic Resonance Elastography |
Neumann, Wiebke | Heidelberg Univ |
Schad, Lothar R. | Heidelberg Univ |
Zöllner, Frank G. | Heidelberg Univ |
Keywords: Magnetic resonance imaging - Other organs, Magnetic resonance imaging - Image reconstruction, Multimodal imaging
Abstract: Magnetic resonance elastography (MRE) is a technique for the quantification of tissue stiffness during MR examinations. It requires consistent methods for mechanical shear wave induction to the region of interest in the human body to reliably quantify elastic properties of soft tissues. This work proposes a novel 3D-printed mechanical actuator using the principle of centrifugal force for wave induction. The driver consists of a 3D-printed turbine vibrator powered by compressed air (located inside the scanner room) and an active driver controlling the pressure of inflowing air (placed outside the scanner room). The generated force of the proposed actuator increases for higher actuation frequencies as opposed to conventionally used air cushions. There, the displacement amplitude decreases with increasing actuation frequency resulting in a smaller signal-to-noise ratio. An initial phantom study is presented which demonstrates the feasibility of the actuator for MRE. The wave-actuation frequency was regulated in a range between 15 Hz and 60 Hz for force measurements and proved sufficiently stable (± 0.3 Hz) for any given nominal frequency. The generated forces depend on the weight of the eccentric unbalance within the turbine and ranged between 0.67 N to 2.70 N (for 15 Hz) and 3.09 N to 7.77 N (for 60 Hz). Therefore, the generated force of the presented actuator increases with rotational speed of the turbine and offers an elegant solution for sufficiently large wave actuation at higher frequencies. In future work, we will investigate an optimal ratio of the weight of unbalance to the size of turbine for appropriately large but tolerable wave actuation for a given nominal frequency.
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FrCT4 Invited Session, Min Room |
Add to My Program |
Body Sensor Networks – Molecules, Radio, and Machine Learning - III |
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Chair: Anzai, Daisuke | Nagoya Inst. of Tech |
Co-Chair: Sugimachi, Masaru | Natl Cardio Center Res. Inst |
Organizer: Balasingham, Ilangko | Oslo Univ. Hospital and Norwegian Univ. of Science and Tech |
Organizer: Anzai, Daisuke | Nagoya Inst. of Tech |
Organizer: Sugimachi, Masaru | Natl Cardio Center Res. Inst |
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14:20-14:35, Paper FrCT4.1 | Add to My Program |
An Improved Design of EEG Monitoring System with Dry Electrodes (I) |
Lee, Seungchan | Gwangju Inst. of Science and Tech |
kumar, Anil | Gwangju Inst. of Science and Tech |
Shin, Younghak | NTNU (Norwegian Univ. of Science and Tech |
Lee, Heung-No | Gwangju Inst. of Science and Tech. (GIST) |
Keywords: Integrated sensor systems, Wearable low power, wireless sensing methods, Bio-electric sensors - Sensor systems
Abstract: In this paper, we aim to introduce our EEG measurement system with dry electrodes. The dry electrode has eighteen spring-loaded probes for dry contact with a scalp without conductive paste. With careful circuit design techniques for lowering noise, the system board was designed to integrate a 32-bit microcontroller, a 24-bit analog-to-digital converter (ADC), and power management circuits for 8-channel EEG acquisition. From the alpha rhythm detection test with the conventional wet electrodes, we show that our system can acquire EEG signals with a sufficient correlation using dry electrodes.
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14:35-14:50, Paper FrCT4.2 | Add to My Program |
Percutaneous Auricular Vagus Nerve Stimulation: Assessment of Sensitivity of Neural Activation to Electrode Position (I) |
Samoudi, Mohammed Amine | Ghent Univ |
Kampusch, Stefan | Vienna Univ. of Tech |
Tanghe, Emmeric | Ghent Univ |
Szeles, Constantin | Univ. Clinic for Surgery, Vienna General Hospital, Medical |
Martens, Luc | Iminds / Ghent Univ |
Kaniusas, Eugenijus | Vienna Univ. of Tech |
Joseph, Wout | Ghent Univ |
Keywords: Physical sensors and sensor systems - Magnetic sensors and systems, Physical sensors and sensor systems - New sensing techniques
Abstract: Percutaneous stimulation of the auricular branch of the vagus nerve (pVNS) is a novel treatment option for acute and chronic pain [1]. However, pVNS stimulations are mainly based on empirical selection of both stimulation regions and parameters, leading to over- or understimulation. Changes in the electrodes’ position can have great effects on the nerves stimulation thresholds. Therefore, sensitivity assessment of neural activation to electrodes’ position is highly needed. Electromagnetic field simulations with neural simulation were performed to investigate the effect of the electrodes’ position within the ear on the excitation threshold in bundled axons. Results show sensitivity of the stimulation thresholds to the electrodes’ positions for up to 15.5% for each 0.1 mm. Results show quantitative sensitivity of the stimulation thresholds to the electrodes’ position, which can affect the important specificity of pVNS. Thus special attention should be paid to the placement of the electrodes for each specific patient.
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14:50-15:05, Paper FrCT4.3 | Add to My Program |
Molecular Communications for Cardiomyocytes (I) |
Lu, Pengfei | Univ. of Oslo and Oslo Univ. Hospital |
Bose, Pritam | Univ. of Oslo and Oslo Univ. Hospital |
Albatat, Mohammad | Univ. of Oslo and Oslo Univ. Hospital |
Balasingham, Ilangko | Oslo Univ. Hospital and Norwegian Univ. of Science And |
Keywords: Wearable antennas and in-body communications
Abstract: The continued miniaturization of electronics makes it realistic to monitor internal cardiac disease processes by wireless implantable medical sensors and actuators incorporated in implantable cardiac devices. In order to deal with some cardiac diseases, this paper introduces the molecular communication methods for cardiac muscle cell communications.
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15:05-15:20, Paper FrCT4.4 | Add to My Program |
A Contact-Less Heart Rate Sensor System for Driver Health Monitoring (I) |
Izumi, Shintaro | Kobe Univ |
Matsunaga, Daichi | Kobe Univ |
Nakamura, Ryota | Kobe Univ |
Kawaguchi, Hiroshi | Kobe Univ |
Yoshimoto, Masahiko | Kobe Univ |
Keywords: Wearable sensor systems - User centered design and applications, Physical sensors and sensor systems - New sensing techniques, New sensing techniques
Abstract: This paper describes a non-contact heart rate monitoring system using a 24-GHz microwave Doppler sensor for driver health monitoring. The objective of this work is to detect an instantaneously heart rate using this non-contact system in a car. The instantaneously heart rate can contribute to prevent heart disasters and to detect mental stress state. However, the Doppler sensor system is very sensitive and it can be easily contaminated by a motion artifact especially while driving. To address this problem, time frequency analysis and autocorrelation method are used. Measurement results show that the Doppler sensor, which is pasted on the clothing surface, can successfully extract the heart rate through clothes. The proposed method achieves 13.1-ms RMS error in heart rate measurement with 11 subjects and 40km/h driving speed on average.
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15:20-15:35, Paper FrCT4.5 | Add to My Program |
Monitoring of Cardiac Diseases by Use of a Wearable Sensor Platform with Capacitive ECG (I) |
Kirchner, Jens | Univ. of Erlangen-Nuremberg |
Fischer, Georg | Univ. of Erlangen-Nuremberg |
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FrCT5 Oral Session, Lee Room |
Add to My Program |
Wearable Sensors and Systems II |
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Chair: Kang, Hongki | KAIST |
Co-Chair: Nam, Yoonkey | Korea Advanced Insitiute of Science and Tech |
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14:20-14:35, Paper FrCT5.1 | Add to My Program |
Inkjet-Printed Gold Nanorods Using Biocompatible Polyelectrolyte Layer-By-Layer Coating for Patterned Photothermal Applications |
Kang, Hongki | KAIST |
Lee, Gu-Haeng | KAIST |
Nam, Yoonkey | Korea Advanced Insitiute of Science and Tech |
Keywords: Wearable body-compliant, flexible and printed electronics, Physical sensors and sensor systems - Thermal sensors and systems, Optical and photonic sensors and systems
Abstract: Photothermal effect using biocompatible nanoparticles with near infrared wavelength light is a versatile tool in biomedical applications due to the temperature sensitivity of cells and good penetrability of the light through many biological systems. However, precise patterning of the nanoparticles on biochips to control the location and intensity of the photothermal effect requires suitable fabrication methods. In this report, we show that inkjet printing of aqueous nanoparticle solution on polyelectrolyte layer-by-layer coated substrates enables micron-scale patterning of gold nanorods, and thus application of photothermal effect with good control.
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14:35-14:50, Paper FrCT5.2 | Add to My Program |
A System for Finger Tremor Quantification in Patients with Parkinson’s Disease |
Bravo Guamán, Marco Fernando | Univ. Pol. Salesiana |
Bermeo Maldonado, Alexander Vinicio | Univ. Pol. Salesiana |
Huerta, Mónica | Simon Bolivar Univ |
Llumiguano, Carlos | Univ. San Francisco and Vozandes Hospital |
Bermeo, Juan Pablo | Univ. Pol. Salesian |
Clotet, Roger | Simón Bolívar Univ |
Soto, Angel | Univ. Pol. Salesiana |
Keywords: Wearable sensor systems - User centered design and applications, New sensing techniques, Wearable body sensor networks and telemetric systems
Abstract: The current diagnosis of Parkinson's disease (PD) is based on a subjective assessment by the specialist. The monitoring of the tremor that presents in the hand index fingers in a patient with Parkinson's is one of the most important parameters to diagnose the evolution of the disease in an objective manner. This research analyze the tremor in the hand index fingers of patients with PD with medication and without medication. A sensor based in a triaxial accelerometer was used to acquire the data produced by the acceleration changes of parkinsonian tremor in the case of three activities: postural tremor, action tremor and rest tremor. Acquired data were processed in Matlab; the data were filtered and the spectral power density (PSD) was estimated with the Burg periodogram. It has been verified that the system presented in this article can accurately detect the parkinsonian tremors of the patients evaluated, additionally has been found that with the medication the tremors do not disappear completely, these remained with the same frequencies of PD but with a very small amplitude.
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14:50-15:05, Paper FrCT5.3 | Add to My Program |
Robust Motion Artefact Resistant Circuit for Calculation of Mean Arterial Pressure from Pulse Transit Time |
Bhattacharya, Tinish | Indian Inst. of Tech. Delhi |
Gupta, Ankesh | Indian Inst. of Tech. Delhi |
Singh, Thoithoi | Indian Inst. of Tech. Delhi |
Roy, Sitikantha | Indian Inst. of Tech. Delhi |
Prasad, Anamika | South Dakota State |
Keywords: Wearable sensor systems - User centered design and applications, Integrated wearable and portable systems, Physiological monitoring - Instrumentation
Abstract: Cuff-less and non-invasive methods of Blood Pressure (BP) monitoring have faced a lot of challenges like stability, noise, motion artefact and requirement for calibration. These factors are the major reasons why such devices do not get approval from the medical community easily. One such method is calculating Blood Pressure indirectly from pulse transit time (PTT) obtained from electrocardiogram (ECG) and Photoplethysmogram (PPG). In this paper we have proposed two novel analog signal conditioning circuits for ECG and PPG that increase stability, remove motion artefacts, remove the sinusoidal wavering of the ECG baseline due to respiration and provide consistent digital pulses corresponding to blood pulses/heart-beat. We have combined these two systems to obtain the PTT and then correlated it with the Mean Arterial Pressure (MAP). The aim was to perform major part of the processing in analog domain to decrease processing load over microcontroller so as to reduce cost and make it simple and robust. We have found from our experiments that the proposed circuits can calculate the Heart Rate (HR) with a maximum error of ~3.0% and MAP with a maximum error of ~2.4% at rest and ~4.6% in motion.
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15:05-15:20, Paper FrCT5.4 | Add to My Program |
A Wearable, EEG-Based Massage Headband for Anxiety Alleviation |
Nair, Chaitanya Muralidharan | National Univ. of Singapore |
Keywords: Wearable sensor systems - User centered design and applications, Physiological monitoring - Instrumentation, Bio-electric sensors - Sensor systems
Abstract: In this work, we would like to discuss our findings obtained from the newly proposed hardware design for anxiety detection and its mitigation where a subject’s state of mind is identified from the neurological data retrieved. A feedback-based network implemented for stress alleviation mainly comprises of a pair of massage motors and RGB light-emitting diode (LED) that activate during conditions of stress detected, a custom-made Electroencephalography (EEG)-sensor and a massage motor circuit both functioning on an Arduino driven platform. The skin electrodes facilitate a hassle-free retrieval of beta waves from the frontal areas that are transmitted wirelessly by a Bluetooth console to a computer post signal amplification and filtration. Rising amplitudes of beta signals that are associated to anxiety have been successfully tackled in three out of four subjects by suppressing the high values due to the massage motor therapy introduced. The motors on sensing high amplitude values exceeding the pre-set threshold limits during the three experiment trials rotate smoothly thus helping one to relax and guaranteeing a higher work performance.
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15:20-15:35, Paper FrCT5.5 | Add to My Program |
TongueToSpeech (TTS): Wearable Wireless Assistive Device for Augmented Speech |
Marjanovic, Nicholas | Univ. of Illinois at Chicago |
Piccinini, Giacomo | Univ. of Illinois at Chicago |
Kerr, Kevin | Univ. of Illinois-Chicago |
Esmailbeigi, Hananeh | Univ. of Illinois at Chicago (UIC) |
Keywords: Wearable body sensor networks and telemetric systems, Wearable sensor systems - User centered design and applications, Wearable low power, wireless sensing methods
Abstract: Speech is an important aspect of human communication; individuals with speech impairment are unable to communicate vocally in real time. Our team has developed the TongueToSpeech (TTS) device with the goal of augmenting speech communication for the vocally impaired. The proposed device is a wearable wireless assistive device that incorporates a capacitive touch keyboard interface embedded inside a discrete retainer. This device connects to a computer, tablet or a smartphone via Bluetooth connection. The developed TTS application converts text typed by the tongue into audible speech. Our studies have concluded that an 8-contact point configuration between the tongue and the TTS device would yield the best user precision and speed performance. On average using the TTS device inside the oral cavity takes 2.5 times longer than the pointer finger using a T9 (Text on 9 keys) keyboard configuration to type the same phrase. In conclusion, we have developed a discrete noninvasive wearable device that allows the vocally impaired individuals to communicate in real time.
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15:35-15:50, Paper FrCT5.6 | Add to My Program |
One Size Fits All Electronics for Insole-Based Activity Monitoring |
Hegde, Nagaraj | The Univ. of Alabama |
Bries, Matthew | The Univ. of Alabama |
Melanson, Ed | Univ. of Colorado at Denver |
Sazonov, Edward | Univ. of Alabama |
Keywords: Wearable sensor systems - User centered design and applications, Integrated sensor systems, Wearable low power, wireless sensing methods
Abstract: Footwear based wearable sensors are becoming prominent in many areas of monitoring health and wellness, such as gait and activity monitoring. In our previous research we introduced an insole based wearable system SmartStep, which is completely integrated in a socially acceptable package. From a manufacturing perspective, SmartStep’s electronics had to be custom made for each shoe size, greatly complicating the manufacturing process. In this work we explore the possibility of making a universal electronics platform for SmartStep – SmartStep 3.0, which can be used in the most common insole sizes without modifications. A pilot human subject experiments were run to compare the accuracy between the one-size fits all (SmartStep 3.0) and custom size SmartStep 2.0. A total of ~10 hours of data was collected in the pilot study involving three participants performing different activities of daily living while wearing SmartStep 2.0 and SmartStep 3.0. Leave one out cross validation resulted in a 98.5% average accuracy from SmartStep 2.0, while SmartStep 3.0 resulted in 98.3% accuracy, suggesting that the SmartStep 3.0 can be as accurate as SmartStep 2.0, while fitting most common shoe sizes.
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FrCT6 Oral Session, Zworykin Room |
Add to My Program |
Cell and Protein Interaction with External Fields I |
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Chair: bonmassar, giorgio | A. A. Martinos Ctr. for Biomedical Imaging |
Co-Chair: Lee, EunAh | Kyung Hee Univ |
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14:20-14:35, Paper FrCT6.1 | Add to My Program |
Electrical Bioimpedance Spectroscopy As Biosensor Technique to Identify Cells Linages and Cell Differentiation Process |
Guerrero Robles, Carla | Inst. Pol. Nacional |
Vázquez Zapién, Gustavo Jesús | Escuela Médico Militar |
Mata Miranda, Mónica Maribel | Escuela Médico Militar |
Noriega González, Jesús Enmanuel | Escuela Médico Militar |
gonzalez, cesar | Univ. Del Ejercito Y Fuerza Aerea |
Keywords: Electric fields - Tissue regeneration, Electromagnetic field effects and cell membrane, Stem cells - Tissue morphogenesis
Abstract: The identification and characterization of diverse cells types and cell differentiation process requires complex techniques as flow cytometry, immunocytochemistry and the exploration of molecular markers; such techniques require infrastructure and qualified personnel. The objective of this study was to analyze the use of Electrical Bioimpedance Spectroscopy (EBIS) measurements as non-complex alternative technique to identify populations of undifferentiated mouse Pluripotent Stem Cells (mPSCs), Mouse Embryonic Fibroblasts (MEFs) and the differentiation process from preadipocytes (3T3-L1) to mature adipocytes. EBIS measurements were compared in populations of cells which were characterized previously using microscopy. The results indicate that EBIS technique has potential sensitivity at certain frequency range to discriminate between both evaluated cell populations and some differentiation process. Additional studies with different concentrations to evaluate quantitatively the sensitivity and specificity of the proposed technique are recommended.
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14:35-14:50, Paper FrCT6.2 | Add to My Program |
Finite-Element Modelling and Preliminary Validation of Microneedle-Based Electrodes for Enhanced Tissue Electroporation |
Houlihan, Ruth | Tyndall National Inst. Univ. Coll. Cork |
Grygoryev, Konstantin | Tyndall National Inst. Univ. Coll. Cork |
Ning, Zhenfei | School of Biochemistry and Cell Biology, Univ. Coll. Cork |
Williams, John Michael | School of Biochemistry and Cell Biology, Univ. Coll. Cork |
Moore, Tom | School of Biochemistry and Cell Biology, Univ. Coll. Cork |
O'Mahony, Conor | Tyndall National Inst. Univ. Coll. Cork |
Keywords: Non-viral gene delivery, Micro- and nano-technology
Abstract: This paper investigates the use of microneedle-based electrodes for enhanced testis electroporation, with specific application to the production of transgenic mice. During the design phase, finite-element software has been used to construct a tissue model and to compare the relative performance of electrodes employing a) conventional flat plates, b) microneedle arrays, and c) invasive needles. Results indicate that microneedle-based electrodes can achieve internal tissue field strengths which are an order of magnitude higher than those generated using conventional flat electrodes, and which are comparable to fields produced using invasive needles. Using a double-sided etching process, conductive microneedle arrays were then fabricated and used in prototype electrodes. In a series of mouse model experiments involving injection of a DNA vector expressing Green Fluorescent Protein (GFP), the performance of flat and microneedle electrodes was compared by measuring GFP expression after electroporation. The main finding, supported by experimental and simulated data, is that use of microneedle-based electrodes significantly enhanced electroporation of testis.
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14:50-15:05, Paper FrCT6.3 | Add to My Program |
EM Fields Comparison between Planar vs. Solenoidal Ums Coil Designs for Nerve Stimulation |
bonmassar, giorgio | A. A. Martinos Ctr. for Biomedical Imaging |
Golestanirad, Laleh | Univ. of Toronto |
Keywords: Micro- and nano-technology, Electromagnetic field effects and cell membrane, Electric fields - Tissue regeneration
Abstract: Micro-magnetic stimulation (uMS) is an emerging neurostimulation technology that promises to revolutionize the therapeutic stimulation of the human nervous system. uMS uses sub-millimeter sized coils that can be implemented in the central nervous system to elicit neuronal activation using magnetically induced electric currents. By the virtue of their microscopic size, uMS coils can be acutely implanted in deep brain structures to deliver therapeutically stimulation with effects analogous to those achieved by State-Of-The-Art deep brain stimulation (DBS). However, uMS technology has inherent advantages that make it particularly appealing for clinical applications. Specifically, uMS induces a focal electric current in the tissue, limiting the extent of activation to a few hundred microns. We recently demonstrated the feasibility of using uMS to elicit neuronal activation in vitro, as well as the possibility of activating neuronal circuitry on the system level in rodents. As uMS is a novel technology, its mechanism(s) of nerve activation, induced field characteristics, and excellent topological features are yet to be explored. In this regard, numerical simulations play a critical role, because they provide an insight into spatial distribution of induced electric fields, which in turn, dictate the dynamics of nerve stimulation. Here we report results of numerical simulations to predict the nerve-stimulation performance of different uMS geometries.
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15:05-15:20, Paper FrCT6.4 | Add to My Program |
Design and Construction of a Synthetic E. Coli Protease Inhibitor Detecting Biomachine |
Boonyalekha, Phenbunya | King Mongkut's Univ. of Tech. Thonburi (KMUTT) |
Meechai, Asawin | King Mongkut's Univ. of Tech. Thonburi (KMUTT) |
Waraho-Zhmayev, Dujduan | King Mongkut's Univ. of Tech. Thonburi (KMUTT) |
Tayapiwatana, Chatchai | Chiang Mai Univ |
Kitidee, Kuntida | Chiang Mai Univ |
Keywords: Synthetic biology
Abstract: Protease inhibitors (PIs) have been used to treat various types of symptoms or diseases. However, current PIs block the protease activity by targeting the protease active site which has been shown to be sensitive to the off-target effect due to crossreactivity with protease homologues. An alternative approach to inhibiting protease activity is to target the substrate, specifically by blocking the substrate cleavage site. We propose to employ synthetic biology approach to create a synthetic E. coli to be used as a protease inhibitor detecting biomachine that can effectively isolate intrabodies, a new generation of protease inhibitor drug. The in vivo selection system, comprised of three biological devices, i.e., protease activity detector, protease generator and protease blocking devices, is based on the ability to transport folded protein of the E. coli twin-arginine translocation (Tat) pathway and antibiotic resistance of TEM-1 β-lactamase (Bla) using as reporter protein. By linking protease degradation to antibiotic resistance, we can isolate the suitable intrabodies simply by plating cells containing appropriate devices on solid agar containing β-lactam ring antibiotics. As a proof of concept, we applied a previously isolated HIV-1 p17 intrabody (scFvp17) that binds to the C-terminus of HIV-1 matrix protein (p17) to our synthetic E. coli. This work demonstrated that binding of scFvp17 to its epitope on p17 can physically interfere with HIV-1 protease activity and inhibit proteolytic cleavage at the p17Δp24 cleavage site when expressed in the designed format. The device was optimized by varying plating conditions such as incubation temperatures, induction levels, and Carbenicillin concentrations which was used as selection pressure. The feasibility of this assay has opened the door to protease inhibitor selection which can be used for various applications such as optimization of the current protease inhibitors and selection of new ones.
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15:20-15:35, Paper FrCT6.5 | Add to My Program |
Determination of Red Blood Cell Fatigue Using Electrodeformation |
Amirouche, Amin | Inst. Des Nanotechnologies De Lyon |
Faivre, Magalie | Inst. Des Nanotechnologies De Lyon |
Chateaux, Jean-François | Univ. Lyon1 Claude Bernard |
Ferrigno, Rosaria | Univ. Claude Bernard Lyon 1 |
Keywords: Cellular force transduction - Cell mechanics, Micro- and nano-technology, Microfluidic applications
Abstract: In this work we used electrodeformation (ED) technique as a new strategy to evaluate the fatigue of healthy human Red Blood Cells (RBCs). Using dielectrophoresis (DEP) forces, we submitted RBCs to a series of elongation and relaxation cycles to model their mechanical stress in the blood circulation and we used their relaxation time as a marker to evaluate their fatigue. In this paper, we first investigated the dependency of the RBC mechanical response upon the experimental parameters, such as the viscosity η of the external medium, the amplitude ΔV of the applied voltage, the duration of the solicitation tsol, the number of solicitations N as well as the resting time trest between two solicitations. The impact of these parameters was evaluated through the analysis of both RBC deformation index D and relaxation time τ. Finally, the optimization of these parameters was used to monitor RBCs fatigue.
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15:35-15:50, Paper FrCT6.6 | Add to My Program |
Analysis of Dielectrophoresis Based 3D-Focusing in Microfluidic Devices with Planar Electrodes |
Hilal-Alnaqbi, ali | United Arab Emirates Univ |
Alazzam, Anas | Khalifa Univ |
Dagher, Sawsan | UAE Univ |
Mathew, Bobby | UAE Univ |
Keywords: Microfluidic applications
Abstract: This article models a dielectrophoresis based approach for achieving 3D focusing, of micro-scale objects, in microfluidic devices. The microfluidic device employs four planar electrodes; two electrodes each on the top and bottom surface of the microchannel and each slightly protrude into the microchannel. Each electrode establishes electric field with the neighboring electrode on the same and opposite surfaces. The dielectrophoretic force pushes the micro-scale objects both the directions transverse to the flow direction to achieve the desired 3D focusing. The developed model accounts for various forces such as that associated with inertia, sedimentation, drag, and dielectrophoresis. Finite difference method is used for calculating the electric field and dielectrophoretic force as well as the displacements of micro-scale objects in the microchannel. Several geometric and operating parameters influence the trajectory of micro-scale objects. There exists a threshold voltage beyond which there is no increase in levitation height.
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15:35-15:50, Paper FrCT6.7 | Add to My Program |
Effect of Laser Diode Light Irradiation on Growth Capability of Human Hair Follicle Dermal Papilla Cells |
Jampa-ngern, Sira | King Mongkut’s Univ. of Tech. Thonburi |
Khantachawana, Anak | King Mongkut's Univ. of Tech. Thonburi |
Viravaidya-Pasuwat, Kwanchanok | King Mongkut's Univ. of Tech. Thonburi |
Suvanasuthi, Saroj | Samitivej Sukhumvit Hospital |
Keywords: Translational issues in tissue engineering and biomaterials, Translational issues in tissue engineering and biomaterials - Cell seeding and viability in scaffolds
Abstract: Low level laser therapy is widely used to relief of pain and inflammation, and restoration of function. The photons of light are absorbed by mitochondrial in cells, lead to increase the production of adenosine triphosphate (ATP), nitric oxide release, blood flow, reactive oxygen species (ROS) [1]. This study has applied laser diode with wavelength of 808 nm to induce dermal papilla cells that located at the base of hair follicle. Dermal papilla is an importance part of hair growth cycle [4, 5]. Cell proliferation and gene expression of dermal papilla cells were observed after treating with light from laser diode. Cell proliferation was analyzed by the number of cells growth in 24 hours. Dermal papilla cells density was used to evaluate the specific growth rate of cell within 5 days. The light dose was selected to be 0.5, 1, 2.5, 4, and 6 J/cm2. The result shows that specific growth rate of cells which were stimulated by laser light is higher than those of the cell without stimulation. The quality of dermal papilla cells was evaluated by gene expression of dermal papilla cells. The real-time polymerase chain reaction (qPCR) was used for observing gene expression. The result of gene expression shows that collagen type 1 (Col1), alkaline phosphatase (Alp), and versican (Vcan) are not increased with treating by light irradiation. Though, the expression of sex determining region y-box 2 (Sox2) increases with applying light irradiation of 0.5 J/cm2, and 1 J/cm2. Moreover, the expression of fibroblast growth factor 7 (Fgf7) increases with applying light irradiation of 0.5 J/cm2, 1 J/cm2, 2.5 J/cm2, and 4 J/cm2. It is noted that expression of Sox2 and Fgf7 are important in hair growth process [4, 5, 17].
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FrCT8 Oral Session, Schwan Room |
Add to My Program |
EEG and Electrical Source Imaging |
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Chair: Ding, Lei | Univ. of Oklahoma |
Co-Chair: Sajib, Saurav Z K | Kyung Hee Univ |
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14:20-14:35, Paper FrCT8.1 | Add to My Program |
Gamma-Variate Modeling of Indicator Dilution Curves in Electrical Impedance Tomography |
Hentze, Benjamin | RWTH Aachen Univ |
Muders, Thomas | Department of Anaesthesiology and Intensive Care Medicine, Univ |
Luepschen, Henning | RWTH Aachen Univ |
Leonhardt, Steffen | RWTH Aachen Univ |
Putensen, Christian | Department of Anaesthesiology and Intensive Care Medicine, Univ |
Walter, Marian | RWTH Aachen Univ |
Keywords: Electrical impedance imaging, Functional image analysis
Abstract: Electrical impedance tomography (EIT) is a noninvasive imaging technique, that can be used to monitor regional lung ventilation (V) in intensive care units (ICU) at bedside. This work introduces a method to extract regional lung perfusion (Q) from EIT image streams in order to quantify regional gas exchange in the lungs. EIT data from a single porcine animal trial, recorded during injection of a contrast agent (NaCl 10%) into a central venous catheter (CVC), are used for evaluation. Using semi-negative matrix factorization (Semi-NMF) a set of source signals is extracted from the data. A subsequent non-linear fit of a gamma-variate model to the source signals results in model signals, describing contrast agent flow through the cardio-pulmonary system. A linear fit of the model signals to the EIT image stream then yields functional images of Q. Additionally, a pulmonary transit function (PTF) and parameters, such as mean transit time (MTT), time to peak (TTP) and area under curve (AUC) are derived. In result, EIT was used to track changes of regional lung ventilation to perfusion ratio (V/Q) during changes of positive end-expiratory pressure (PEEP). Furthermore, correlations of MTT and AUC with cardiac output (CO) indicate that CO measurement by EIT might be possible.
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14:35-14:50, Paper FrCT8.2 | Add to My Program |
Localization of Stereoelectroencephalography Signals Using a Finite Difference Complete Electrode Model |
Hyde, Damon | Boston Children's Hospital and Harvard Medical School |
Tomas-Fernandez, Xavier | Harvard Univ |
Stone, Scellig | Boston Children's Hospital and Harvard Medical School |
Peters, Jurriaan | Boston Children's Hospital |
Warfield, Simon K. | Harvard Medical School |
Keywords: Electrical source brain imaging
Abstract: Surgical intervention in epilepsy aims to eliminate seizures in refractory patients by resecting the tissue responsible for seizure onset. Stereo-electroencephalography (sEEG) provides highly accurate but invasive electrophysiological measurements using narrow multi-contact electrodes implanted stereotactically through small holes in the skull. However, the three dimensional nature of sEEG measurements make observed seizure onsets difficult to associate with physical cortical regions. Three dimensional source localization from sEEG measurements can improve the interpretation of this data, but requires more accurate modeling as compared to localization from scalp EEG. Here, we present a finite difference approach that models the contact impedance and physical extent of each electrode (the so-called complete electrode model), to localize brain electrical activity from sEEG measurements. We applied this model to MRI and CT in a patient with intractable epilepsy, and reconstructed activity associated with multiple types of recurrent ictal spikes observed in sEEG. Independently, the neurosurgeon resected the clinically determined seizure focus, creating a resection cavity, and rendering the patient free of seizures. Our localization placed the seizure focus at a focal region in the occipital lobe, entirely contained within the resection region.
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14:50-15:05, Paper FrCT8.3 | Add to My Program |
Spatial Regularization Based on Dmri to Solve EEG/MEG Inverse Problem |
Belaoucha, Brahim | Univ. Côte D'azur, Inria |
Papadopoulo, Théodore | INRIA Sophia-Antipolis |
Keywords: EEG imaging, MEG imaging, Electrical source brain imaging
Abstract: In this paper, we present a new approach to reconstruct dipole magnitudes of a distributed source model for magnetoencephalographic (MEG) and electroencephalographic (EEG). This approach is based on the structural homogeneity of the cortical regions which are obtained using diffusion MRI (dMRI). First, we parcellate the cortical surface into functional regions using structural information. Then, we use a weighting matrix that relates the dipoles’ magnitudes of sources inside these functional regions. The weights are based on the region’s structural homogeneity. Results of the simulated and real MEG measurement are presented and compared to classical source reconstruction methods.
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15:05-15:20, Paper FrCT8.4 | Add to My Program |
EEG Fluctuations of Wake and Sleep in Mild Cognitive Impairment |
O'Keeffe, Johnny | The Unversity of Oklahom |
Carlson, Barbara | The Unversity of Oklahom |
DeStefano, Lisa | The Unversity of Oklahom |
Wenger, Michael | The Univ. of Oklahoma |
Craft, Melissa | The Unversity of Oklahom |
Hershey, Linda | The Unversity of Oklahom |
Hughes, Jeremy | The Unversity of Oklahom |
Wu, Dee | Univ. of Oklahoma Health Sciences |
Ding, Lei | Univ. of Oklahoma |
Yuan, Han | Univ. of Oklahoma |
Keywords: EEG imaging, Electrical source brain imaging, Brain image analysis
Abstract: Amnestic Mild Cognitive Impairment (aMCI), a condition in which the memory functions of cognition are significantly impaired, is an established risk factor for Alzheimer’s disease. Electroencephalography (EEG) is a tool capable of measuring the dynamics of the brain’s neural networks, and is thus an important means in analysis and understanding of aMCI. In this proof-of-concept study, we compared the brain activation patterns of ten aMCI subjects with those of four healthy subjects during sleep by employing a 64-channel EEG data collection system. The power spectrum was analyzed to identify sleep stages, while spectral topography and source imaging techniques were employed to study the fluctuating patterns of the brain. Results of this study show an increase in activation power across all sleep stages in the delta and theta frequency bands alongside a decrease in alpha band activity for aMCI subjects. Source imaging analysis of the resting EEG identified default mode network, which becomes decoupled as sleep stages deepen. In the proof-of-concept study, our exploratory analysis demonstrated the feasibility of imaging dynamic network organization using EEG in aMCI.
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15:20-15:35, Paper FrCT8.5 | Add to My Program |
Computation of Surface Laplacian for Tri-Polar Ring Electrodes on High-Density Realistic Geometry Head Model |
MA, JUNWEI | Univ. of Oklahoma |
Yuan, Han | Univ. of Oklahoma |
Sunderam, Sridhar | Univ. of Kentucky |
Besio, W. G. | Univ. of Rhode Island |
Ding, Lei | Univ. of Oklahoma |
Keywords: EEG imaging
Abstract: Neural activity inside the human brain generate electrical signals that can be detected on the scalp. Electroencephalograph (EEG) is one of the most widely utilized techniques helping physicians and researchers to diagnose and understand various brain diseases. Due to its nature, EEG signals have very high temporal resolution but poor spatial resolution. To achieve higher spatial resolution, a novel tri-polar concentric ring electrode (TCRE) has been developed to directly measure Surface Laplacian (SL). The objective of the present study is to accurately calculate SL for TCRE based on a realistic geometry head model. A locally dense mesh was proposed to represent the head surface, where the local dense parts were to match the small structural components in TCRE. Other areas without dense mesh were used for the purpose of reducing computational load. We conducted computer simulations to evaluate the performance of the proposed mesh and evaluated possible numerical errors as compared with a low-density model. Finally, with achieved accuracy, we presented the computed forward lead field of SL for TCRE for the first time in a realistic geometry head model and demonstrated that it has better spatial resolution than computed SL from classic EEG recordings.
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FrCT9 Oral Session, Plonsey Room |
Add to My Program |
Neural Signal Processing II |
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Chair: Wheeler, Bruce | Univ. of Florida |
Co-Chair: CHAN, Leanne LH | City Univ. of Hong Kong |
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14:20-14:35, Paper FrCT9.1 | Add to My Program |
Independent Component Analysis-Based Spatial Filtering Improves Template-Based SSVEP Detection |
Nakanishi, Masaki | Univ. of California San Diego |
Wang, Yijun | Inst. of Semiconductors, Chinese Acad. of Sciences |
Hsu, Sheng-Hsiou | Univ. of California, San Diego |
Wang, Yu-Te | Univ. of California San Diego |
Jung, Tzyy-Ping | Univ. of California San Diego |
Keywords: Brain-computer/machine interface, Neural signal processing, Neural signals - Blind source separation (PCA, ICA, etc.)
Abstract: This study proposes a new algorithm to detect steady-state visual evoked potentials (SSVEPs) based on a template-matching approach combined with independent component analysis (ICA)-based spatial filtering. In recent studies, the effectiveness of the template-based SSVEP detection has been demonstrated in a high-speed brain-computer interface (BCI). Since SSVEPs can be considered as electroencephalogram (EEG) signals generated from underlying brain sources independent from other activities and artifacts, ICA has great potential to enhance the signal-to-noise ratio (SNR) of SSVEPs by separating them from artifacts. This study proposes to apply the ICA-based spatial filters to test data and individual templates obtained by averaging training trials, and then to use the correlation coefficients between the filtered data and templates as features for SSVEP classification. This study applied the proposed method to a 40-class SSVEP dataset to evaluate its classification accuracy against those obtained by conventional canonical correlation analysis (CCA)- and extended CCA-based methods. The study results showed that the ICA-based method outperformed the other methods in terms of the classification accuracy. Furthermore, its computational time was comparable to the CCA-based method, and was much shorter than that of the extended CCA-based method.
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14:35-14:50, Paper FrCT9.2 | Add to My Program |
Using Monkey Hand Exoskeleton to Explore Finger Passive Joint Movement Response in Primary Motor Cortex |
Qian, Kai | Illinois Inst. of Tech |
Antonio dos Anjos Jr., Luiz | Illinois Inst. of Chicago |
Balasubramanian, Karthikeyan | Univ. of Chicago |
Stilson, Kelsey | The Univ. of Chicago |
Balcer, Carrie Anne | Univ. of Chicago |
Hatsopoulos, Nicholas | Univ. of Chicago |
Kamper, Derek | Rehabilitation Inst. of Chicago |
Keywords: Neural signals - Coding, Neuromuscular systems - Peripheral mechanisms, Motor neuroprostheses - Robotics
Abstract: While neurons in primary motor cortex (M1) have been shown to respond to sensory stimuli, exploration of this phenomenon has proven challenging. Accurate and repeatable presentation of sensory inputs is difficult. Here, we describe a novel paradigm to study response to joint motion and fingertip force. We employed a custom exoskeleton to drive index finger metacarpophalangeal joint of a macaque to follow sinusoid trajectories at 4 different frequencies (0.2, 0.5, 1, 2Hz) and 2 movement ranges (68.4, 34.2 degrees). We highlight results of a specific M1 unit that displayed sensitivity to direction (more active during flexion than extension), frequency (greater firing rate at higher frequencies), and movement amplitude (higher rate at larger amplitude). Joint movement trajectories were accurately reconstructed from this single unit with mean R2 =0.64 ± 0.13. The exoskeleton holds promise for examination of sensory feedback. In addition, it can be used as an external device controlled by a brain-machine interface (BMI) system. The proprioceptive related units in M1 may contribute to improving BMI control performance.
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14:50-15:05, Paper FrCT9.3 | Add to My Program |
Specific CA3 Neurons Decode Neural Information of Dentate Granule Cells Evoked by Paired-Pulse Stimulation in Co-Cultured Networks |
Poli, Daniele | Univ. of California, Irvine |
DeMarse, Thomas B. | Univ. of Florida |
Wheeler, Bruce | Univ. of Florida |
Brewer, Gregory | Univ. of California Irvine, Southern Illinois Univ |
Keywords: Neural signals - Coding, Neural interfaces - Microelectrode technology, Neural interfaces - Cellular
Abstract: CA3 and dentate gyrus (DG) neurons are cultured in two-chamber devices on multi-electrode arrays (MEAs) and connected via micro-tunnels. In order to evoke time-locked activity, paired-pulse stimulation is applied to 22 different sites and repeated 25 times in each well in 5 MEA co-cultures and results compared to CA3-CA3 and DG-DG networks homologous controls. In these hippocampal sub-regions, we focus on the mechanisms underpinning a networks ability to decode the identity of site specific stimulation from analysis of evoked network responses using a support vector machine classifier. Our results indicate that a pool of CA3 neurons is able to reliably decode the identity of DG stimulation site information.
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15:05-15:20, Paper FrCT9.4 | Add to My Program |
Information Transmission in the Primary Visual Cortex of Retinal Degenerated Rats |
Wang, Yi | City Univ. of Hong Kong |
chen, ke | Univ. of Electronic Science and Tech. of China |
CHAN, Leanne LH | City Univ. of Hong Kong |
Keywords: Neural signals - Information theory, Neural stimulation, Sensory neuroprostheses - Visual
Abstract: To study the information transmission in the primary visual cortex (V1) of retinal degenerated (RD) models, wild type (WT) and RD rats were used in the experiments. The neural response in V1 was recorded extracellularly while the flicker with varied intensity levels was given as the visual stimulus. The mutual information (MI) and normalized mutual information (NMI) were determined for every isolated neuron, in order to quantify the amount and efficiency of information transmission in V1 of both control and experimental groups. The results showed that, on one hand, the RD group manifested relatively decreased information transmission amount and efficiency, comparing to the control group; On the other hand, it also implied that even for the RD rat, whose early stage of visual system was impaired, the later parts of visual system, especially the primary visual cortex, were still able to capture the information on visual stimulation, thus they can be utilized for restoring the visual ability, for example, via the visual prosthesis. In addition, it certainly requires more experiments for testifying and extending those results and implications.
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15:20-15:35, Paper FrCT9.5 | Add to My Program |
Sparse Coding of ECoG Signals Identifies Interpretable Components for Speech Control in Human Sensorimotor Cortex |
Bouchard, Kristofer E. | LBNL |
Bujan, Alejandro F | UC Berkeley |
Chang, Edward | UCSF |
Sommer, Friedrich | Univ. of California Berkeley |
Keywords: Neural signals - Blind source separation (PCA, ICA, etc.), Brain functional imaging - Spatial-temporal dynamics, Neural signals - Nonlinear analysis
Abstract: The concept of sparsity has proven useful to understanding elementary neural computations in sensory systems. However, the role of sparsity in motor regions is poorly understood. Here, we investigated the functional properties of sparse structure in neural activity collected with high-density electrocorticography (ECoG) from speech sensorimotor cortex (vSMC) in neurosurgical patients. Using independent components analysis (ICA), we found individual components corresponding to individual major oral articulators (i.e., Coronal Tongue, Dorsal Tongue, Lips), which were selectively activated during utterances that engaged that articulator on single trials. Some of the components corresponded to spatially sparse activations. Components with similar properties were also extracted using convolutional sparse coding (CSC), and required less data pre-processing. Finally, individual utterances could be accurately decoded from vSMC ECoG recordings using linear classifiers trained on the high-dimensional sparse codes generated by CSC. Together, these results suggest that sparse coding may be an important framework and tool for understanding sensory-motor activity generating complex behaviors, and may be useful for brain-machine interfaces.
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15:35-15:50, Paper FrCT9.6 | Add to My Program |
A New EMG-Based Index towards the Assessment of Elbow Spasticity for Post-Stroke Patients |
Wang, Lei | Shenzhen Inst. of Advanced Tech. Chinese Acad. of Sc |
Guo, Xin | Hebei Univ. of Tech |
Fang, Peng | Shenzhen Inst. of Advanced Tech. Chinese Acad. of S |
Wei, Yue | Shenzhen Inst. of Advanced Tech. Chinese Acad. of S |
Samuel, Oluwarotimi Williams | Shenzhen Inst. of Advanced Tech |
Huang, Pin-Gao | Chinese Acad. of Sciences |
Geng, Yanjuan | Shenzhen Inst. of Advanced Tech |
Wang, Hui | Shenzhen Inst. of Advanced Tech. Chinese Acad. of S |
Li, Guanglin | Shenzhen Inst. of Advanced Tech |
Keywords: Neural signal processing, Neurorehabilitation, Neurological disorders - Diagnostic and evaluation techniques
Abstract: The commonly used method for grading spasticity in clinical applications is Modified Ashworth Scale (MAS). The MAS-based method depends on the subjective evaluations and the experience of physicians, which may lead to imprecise and inconsistent evaluations. In this study, we propose a novel index (A-ApA, which was calculated with the root mean square (RMS) of agonist muscle activity by the mean between the RMS of agonistic and antagonistic muscle activations extracted from surface electromyography (sEMG) signals to quantitatively assess elbow spasticity. 39 post-stroke patients with elbow spasticity caused by hemiplegia participated in the experiments, and their elbow spasticity was assessed with MAS by one experienced physiotherapist. Patients were thereafter divided into four groups according to the MAS scales. The sEMG signals were recorded simultaneously on the patients’ biceps and triceps when they extended or bended their elbows passively. The correlations between MAS and RMS of sEMG signals as well as the newly proposed index were calculated. The results demonstrated that the correlation between the MAS and the sEMG-based index in the assessment of elbow spasticity was significant. This suggests that the EMG-based index would be helpful for the assessment of spasticity.
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FrCT10 Oral Session, Schmitt Room |
Add to My Program |
General and Theoretical Informatics - Data Mining I |
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Chair: Kim, Soochan | Hankyong National Univ |
Co-Chair: Fotiadis, Dimitrios I. | Univ. of Ioannina |
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14:20-14:35, Paper FrCT10.1 | Add to My Program |
Gamaid: Greedy CP Tensor Decomposition for Supervised EHR-Based Disease Trajectory Differentiation |
Henderson, Jette | The Univ. of Texas at Austin |
Ho, Joyce C. | Emory Univ |
Ghosh, Joydeep | Univ. of Texas, Austin |
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14:35-14:50, Paper FrCT10.2 | Add to My Program |
A Computational Approach for the Estimation of Heart Failure Patients Status Using Saliva Biomarkers |
Tripoliti, Evanthia | Univ. of Ioannina |
Papadopoulos, Theofilos | Unit of Medical Tech. and Intelligent Information Systems, |
Karanasiou, Georgia | Inst. of Molecular Biology and Biotechnology, FORTH, Ioannin |
Kalatzis, Fanis | Department of Biomedical Res. Inst. of Molecular Biolog |
Goletsis, Yorgos | Univ. of Ioannina |
Bechlioulis, Aris | Michaelidion Cardiac Center, Univ. of Ioannina, and 2nd Dep |
Ghimenti, Silvia | Univ. of Pisa, Department of Chemistry and Industrial Chemi |
Lomonaco, Tommaso | Univ. of Pisa, Department of Chemistry and Industrial Chemi |
Bellagambi, Francesca | Univ. of Pisa, Department of Chemistry and Industrial Chemi |
Trivella, Maria G. | Istituto Di Fisiologia Clinica-CNR, Pisa |
Fuoco, Roger | Univ. of Pisa, Department of Chemistry and Industrial Chemi |
Marzilli, Mario | Azienda Ospedaliera-Univ. Pisana, Cardiothoracic and Vas |
Scali, Maria Chiara | Azienda Ospedaliera-Univ. Pisana, Cardiothoracic and Vas |
Naka, Katerina | Univ. of Ioannina |
Abdelhamid, Errachid | Univ. De Lyon, Inst. De Sciences Analytiques (ISA) |
Fotiadis, Dimitrios I. | Univ. of Ioannina |
Keywords: General and theoretical informatics - Data mining, General and theoretical informatics - Knowledge modeling, General and theoretical informatics - Machine learning
Abstract: The aim of this work is to present a computational approach for the estimation of the severity of heart failure (HF) in terms of New York Heart Association (NYHA) class and the characterization of the status of the HF patients, during hospitalization, as acute, progressive or stable. The proposed method employs feature selection and classification techniques. However, it is differentiated from the methods reported in the literature since it exploits information that biomarkers fetch. The method is evaluated on a dataset of 29 patients, through a 10-fold-cross-validation approach. The accuracy is 94 and 77% for the estimation of HF severity and the status of HF patients during hospitalization, respectively.
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14:50-15:05, Paper FrCT10.3 | Add to My Program |
Exploration of Unsupervised Feature Selection Methods to Predict Chronological Age of Individuals by Utilising CpG Dinucleotics from Whole Blood |
Sarac, Ferdi | Northumbria Univ. at Newcastle |
Seker, Huseyin | The Univ. of Northumbria at Newcastle |
Bouridane, Ahmed | Northumbria Univ |
Keywords: General and theoretical informatics - Big data analytics, General and theoretical informatics - Data mining, General and theoretical informatics - Unsupervised learning method
Abstract: Identification of the age of individuals from epigenetic markers can reveal vital information for criminal investigation, disease prevention, and extension of life. DNA methylation changes are highly associated with chronological age and the process of disease development. Computational methods such as clustering, feature selection and regression can be utilised to construct quantitative model of aging. In this study, we utilised 473034 CpG biomarkers from whole blood of 656 individuals aged 19 to 101 to construct predictive models and we treat the development of this age predictive model as extremely high-dimensional regression problem that is relatively understudied. Unlike semi supervised and supervised feature selection methods, unsupervised feature selection methods are generally good at removing irrelevant features that can act as noise. In this study, along with the entire feature set, four different unsupervised feature selection methods (USFSMs) are therefore considered for the quantitative prediction of human ages. Since USFSMs are independent of any predictive method, support vector regression is then used to evaluate the prediction performances of the unsupervised feature selection methods. We proposed a novel k-means based unsupervised feature selection method to predict human ages by utilising CpG dinucleotides. Experimental results have validated the effectiveness of the proposed method as the optimum number of the CpG dinucleotides is found to be only 41 that corresponds to only 0.0087% of the entire feature space. To the best of our knowledge, this is the first study that presents exploration and comprehensive comparison of USFSMs in very high dimensional regression problems, particularly in epigenetic biomedical domain for the prediction of chronological age from changes in DNA methylation.
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15:05-15:20, Paper FrCT10.4 | Add to My Program |
Wrapper Method for Feature Selection to Classify Cardiac Arrhythmia |
Mustaqeem, Anam | Univ. of Engineering and Tech. Taxila |
Anwar, Syed | Univ. of Engineering and Tech |
Majid, Muhammad | Univ. of Engineering and Tech. Taxila |
Khan, Abdul Rashid | POF Hospital, WAH CANTT |
Keywords: General and theoretical informatics - Machine learning, Health Informatics - Computer-aided decision making, Health Informatics - Decision support methods and systems
Abstract: Efficient monitoring of cardiac patients can save tremendous amount of lives. Cardiac disease prediction and classification has gained utmost significance in this regard during the past few years. This paper presents a predictive model for classification of arrhythmias. The model works by selecting best features using wrapper algorithm around random forest, followed by implementing various machine learning classifiers on the selected features. Cardiac arrhythmia dataset from University of California, Irvine (UCI) machine learning repository has been used for the experimental purpose. After normalizing the data, repeated cross validation with 10 folds is applied on support vector machine (SVM), K nearest neighbor (KNN), Naïve Bayes, random forest, and Multi-Layer perceptron (MLP). The experimental results demonstrate that MLP beats other classifiers by achieving an average accuracy of 78.26%, while accuracies calculated for KNN and SVM are 76.6% and 74.4% respectively, outperforming the accuracies of previous models.
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15:20-15:35, Paper FrCT10.5 | Add to My Program |
Prediction and Imputation in Irregularly Sampled Clinical Time Series Data Using Hierarchical Linear Dynamical Models |
Sengupta, Abhishek | Walmart Labs India |
ap, Prathosh | XEROX Res. CENTRE INDIA |
Shukla, Satya Narayan | Univ. of Massachusetts Amherst |
Rajan, Vaibhav | Yen4Ken Software Pvt. Ltd |
Reddy, Chandan K | Virginia Tech |
Shukla, Satya Narayan | Univ. of Massachusetts Amherst |
Keywords: General and theoretical informatics - Predictive analytics, General and theoretical informatics - Machine learning, General and theoretical informatics - Statistical data analysis
Abstract: Clinical time series, comprising of repeated clinical measurements provide valuable information of the trajectory of patients' condition. Linear dynamical systems (LDS) are used extensively in science and engineering for modeling time series data. The observation and state variables in LDS are assumed to be uniformly sampled in time with a fixed sampling rate. The observation sequence for clinical time series is often irregularly sampled and LDS do not model such data well. In this paper, we develop two LDS--based models for irregularly sampled data. The key idea is to incorporate a temporal difference variable within the state equations of LDS whose parameters are estimated using observed data. Our models are evaluated on prediction and imputation tasks using real irregularly sampled clinical time series data and are found to outperform state-of-the-art techniques.
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15:35-15:50, Paper FrCT10.6 | Add to My Program |
Identifying Frauds and Anomalies in Medicare-B Dataset |
Seo, Jiwon | UNIST |
Mendelevitch, Ofer | LendUp.com |
Keywords: Public Health Informatics - Non-medical data analytics in public health
Abstract: Healthcare industry is growing at a rapid rate to reach a market value of 7 trillion dollars world wide. At the same time, fraud in healthcare is becoming a serious problem, amounting to 5% of the total healthcare spending, or 100 billion dollars each year in US. Manually detecting healthcare fraud requires much effort. Recently, machine learning and data mining techniques are applied to automatically detect healthcare frauds. This paper proposes a novel PageRank-based algorithm to detect healthcare frauds and anomalies. We apply the algorithm to Medicare-B dataset, a real-life data with 10 million healthcare insurance claims. The algorithm successfully identifies tens of previously unreported anomalies.
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FrCT11 Oral Session, Greatbatch Room |
Add to My Program |
Models of Cardiac Function and Blood Flow |
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Chair: Avolio, Alberto P | Macquarie Univ |
Co-Chair: Shimayoshi, Takao | Kyushu Univ |
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14:20-14:35, Paper FrCT11.1 | Add to My Program |
A Computational Model of Myocardial Microcirculation Including Interstitial Flow |
Shimayoshi, Takao | Kyushu Univ |
Yamamoto, Yuta | Kyoto Univ |
Matsuda, Tetsuya | Kyoto Univ |
Keywords: Organs and medical devices - Multiscale modeling and the physiome, Organ modeling
Abstract: Contributions of interstitial fluid (ISF) flow within the myocardial microcirculation is not well understood despite its importance due to difficulties in measurements. For analysing a contribution of interstitial fluid flow within myocardial microcirculation, we developed a computational model of myocardial microcirculation by introducing convection by the ISF flow into an existing myocardial microcirculation model, and performed simulations with varied ISF flows in normal and hypoperfusion conditions. Simulation results show that the ISF flow has a contribution only with low capillary flow. This might suggest partial comensation of oxygen supply by the ISF flow under ischemic conditions.
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14:35-14:50, Paper FrCT11.2 | Add to My Program |
PWPSim: A New Simulation Tool of Pulse Wave Propagation in the Human Arterial Tree |
Xiao, Hanguang | Chongqing Univ. of Tech |
Butlin, Mark | Macquarie Univ |
Tan, Isabella | Macquarie Univ |
Avolio, Alberto P | Macquarie Univ |
Keywords: Model building - Algorithms and techniques for systems modeling
Abstract: Hemodynamic simulation enhances investigations of pulse wave propagation phenomena and enables validation of new methods of pulse wave analysis. However, such simulation systems or tools are not readily available nor easily accessible. In this study, a new simulation tool of pulse wave propagation in the human arterial tree was developed based on a transmission line model (TLM). This paper describes the theory of TLM of the human arterial tree used by this simulation. The results are a display of the main functions and simulation results of this tool. This tool allows simulation of pulse wave propagation with capability to change the range of parameters, such as heart rate, mean flow and left ventricular ejection time, body height, arterial radius and wall thickness,arterial viscoelasticity, peripheral resistance and compliance. It also accounts for the nonlinear elasticity of arteries. The simulation results are displayed as 2D and 3D figures of blood pressure and flow waveforms, input impedance and pressure transfer function between aorta and femoral artery, including systolic blood pressure, diastolic blood pressure, pulse pressure, carotid-femoral pulse wave velocity, brachial-ankle pulse wave velocity and ankle-brachial index. It is a useful and interactive simulation tool of pulse wave propagation in the systematic arterial tree.
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14:50-15:05, Paper FrCT11.3 | Add to My Program |
Global Sensitivity Analysis for Developing Biological Models: Application to K+ Channel Model in Mouse Ventricular Myocytes |
DU, DONGPING | Texas Tech. Univ |
Du, Yuncheng | Clarkson Univ |
Keywords: Model building - Sensitivity analysis, Model building - Algorithms and techniques for systems modeling
Abstract: Mathematical models of cardiac myocytes are highly nonlinear and involve a large number of model parameters. The parameters are estimated using experimental data, which are often corrupted by noise and uncertainty. Such uncertainty can be propagated onto model parameters during model calibration, which further affects model reliability and credibility. In order to improve model accuracy, it is important to quantify and reduce the uncertainty in model response resulting from parametric uncertainty. Sensitivity analysis is a key technique to investigate the significance of parametric uncertainty and its effect on model responses. This can identify and rank most sensitive parameters, and evaluate the effect of uncertainty on model outputs. In this work, a global sensitivity analysis is developed to determine the significance of parametric uncertainty on model responses using Sobol indices. This method is applied to nonlinear K+ channel models of mouse ventricular myocytes to demonstrate the efficacy of the developed algorithm.
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15:05-15:20, Paper FrCT11.4 | Add to My Program |
A Generic Cardiac Biventricular Fluid-Electromechanics Model |
Ahmad Bakir, Azam | The Univ. of New South Wales |
Al Abed, Amr | Univ. of New South Wales |
Lovell, Nigel H. | Univ. of New South Wales |
Dokos, Socrates | Univ. of New South Wales |
Keywords: Models of organ physiology, Organ modeling, Organs and medical devices - Multiscale modeling and the physiome
Abstract: We present a fully-coupled fluid-electromechanics model of the heart using a generic biventricular structure to provide a tool for future multiphysics interaction studies. A simplified Purkinje fibre structure was embedded within the myocardium along with transmural variation of action potential duration to obtain realistic activation and relaxation sequences. To ease computational requirements, phenomenological action potential and excitation- contraction formulations were chosen, and coupled to transverse isotropic hyperelastic myocardial material physics. The action potential propagation was discretised within the material frame to achieve electromechanical coupling with gap junction-controlled propagation. Blood haemodynamics was represented by incompressible Navier Stokes equations, whereby, the endocardial displacement deforms the blood domain, whilst blood pressure and viscous stress exert load on the myocardium. Realistic electrical activation and relaxation sequences were achieved along with basic cardiac mechanical properties such as torsion and apex displacement. The pressure-volume loops for both ventricles matched known values, and vortex formation was noted during the filling phase. The model could facilitate a better understanding of multiphysics and biventricular interactions under pathologic conditions and help formulate better treatments.
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15:20-15:35, Paper FrCT11.5 | Add to My Program |
Effects of Island-Distribution of Mid-Cardiomyocytes on Ventricular Electrical Excitation Associated with the KCNQ1-Linked Short QT Syndrome |
Luo, Cunjin | Harbin Inst. of Tech. School of Computer Science and T |
Wang, Kuanquan | Harbin Inst. of Tech |
Zhang, Henggui | Harbin Inst. of Tech. School of Computer Science and T |
Zhang, Yue | Harbin Engineering Univ |
Keywords: Modeling of cell, tissue, and regenerative medicine - Ionic modeling, Modeling of cell, tissue, and regenerative medicine - Cells, Synthetic biology
Abstract: Abstract—Aims: Short QT syndrome (SQTS) is a new genetic disorder of the electrical system of the heart. To date, there are six gene mutations in ion channels underlying SQTS. However, functional effects of spatial heterogeneities, such as island-distribution of mid-cardiomyocytes (M island) on ventricular electrical excitation in SQTS condition are poorly understood or even not understood at all. Therefore, this study used computational modelling to investigate such possible effects. Methods: The spatial heterogeneities of ventricular tissue was studied by using ten Tusscher et al. model. The model was modified to simulate changes to IKs based on experimental observations of KCNQ1 V307L mutation in SQT2 condition. Cell models were coupled to construct a strand tissue, among which 35% were mid-cardiomyocytes, either distributed in island form or in band form, 25% were endocardial (ENDO), and the rest part were epicardial (EPI) cells. Results: In simulations, the QT interval was shortened due to the KCNQ1 V307L mutation. The model with M band form failed to reproduce a markedly increase in the T-wave height. However, the model with M island form was able to produce a markedly increased T-wave height with the V307L mutation, matching the major features of SQT clinical ECGs. Conclusions: This study substantiates a causal link between the M island and T-wave amplitude in the KCNQ1-linked short QT syndrome.
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15:35-15:50, Paper FrCT11.6 | Add to My Program |
Hyperthermia Dependence of Cardiac Conduction Velocity in Rat Myocardium: Optical Mapping and Cardiac Near Field Measurements |
Pollnow, Stefan | Karlsruhe Inst. of Tech |
Arnold, Robert | Medical Univ. of Graz, Austria |
Werber, Matthias | Karlsruhe Inst. of Tech. (KIT) |
Doessel, Olaf | Karlsruhe Inst. of Tech. (KIT) |
Seemann, Gunnar | Univ. Heart Center Freiburg - Bad Krozingen |
Keywords: Cardiac electrophysiology - Structural disease, Cardiac electrophysiology - Defibrillation, ablation, and cardioversion, Cardiac mechanics, structure & function - Cardiac structure from imaging
Abstract: Hyperthermia during radiofrequency ablation causes reversible and irreversible changes of the electrophysiological properties of cardiac tissue. However, the mechanisms are incompletely understood. We studied changes of conduction velocity (CV) in rat myocardium under hyperthermic conditions from macroscopic to microscopic scale by using simultaneous optical mapping and a miniaturized electrode array. Atrial preparations from five rats were superfused at tissue bath temperatures between 36.7°C and 43.8°C. Optical mapping data showed an elevated median CV by 21% when increasing the temperature from 36.7°C to 42.0°C. CV did not increase above 42.0°C. Electrical measurements revealed a similar temperature dependence of CV between 36.7°C and 42.0°C, i.e. an increase of median CV by 26%. The consolidation of optical and electrical data in this study allowed investigation of excitation during global hyperthermia. Macroscopic optical mapping and microscopic electrical measurements demonstrated that hyperthermia strongly influenced electrical propagation at a microscopic scale.
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FrCT13 Minisymposium, Dunn Room |
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Contemporary Diagnostic Devices in Traditional Eastern Medicine: Overview
of the Research Activities at KIOM |
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Chair: Kim, Jaeuk U | Korean Inst. of Oriental Medicine |
Co-Chair: Kim, Keun Ho | Korea Inst. of Oriental Medicine |
Organizer: Kim, Jaeuk U | Korean Inst. of Oriental Medicine |
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14:20-14:35, Paper FrCT13.1 | Add to My Program |
Biofield Research and Exogenous Features of Bioelectricity (I) |
Kim, Jaeuk U | Korean Inst. of Oriental Medicine |
Jun, Min-Ho | KIOM |
Bae, Jang-Han | Korea Inst. of Oriental Medicine, KAIST |
Ku, Boncho | Korea Inst. of Oriental Medicine (KIOM) |
Kim, Jungyoon | KOREA Inst. OF ORIENTAL MEDICINE |
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14:35-14:50, Paper FrCT13.2 | Add to My Program |
Development of 3D Asymmetry Analysis System for Human Body Shape (I) |
Jang, Jun-Su | Korea Inst. of Oriental Medicine |
Keywords: Diagnostic devices - Physiological monitoring, FNIR and near-infrared scanning and assessment, Plethysmography
Abstract: Recently, the popularity of 3D camera technology has enabled low-cost 3D scanning and analysis for human appearance. In this paper, we introduce a system that uses commercial depth camera to scan the human body and analyzes scanned data using an automated algorithm. Sagittal plane setup is important for asymmetry analysis. Using the proposed 3D image analysis method, we automatically set the sagittal plane of the human body. The repeatability of the asymmetry analysis is verified experimentally.
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14:50-15:05, Paper FrCT13.3 | Add to My Program |
Classification of Upper Respiratory Tract Infection Patients by Tongue Image Analysis (I) |
Choi, Woosu | Korea Inst. of Oriental Medicine |
Kim, Keun Ho | Korea Inst. of Oriental Medicine |
Keywords: Diagnostic devices - Physiological monitoring
Abstract: The images of the patients with upper respiratory tract infection (UTRI) before and after the treatment were analyzed to find the index of the tongue affected UTRI, and a discriminant model was made to identify the tongue of the patients with UTRI and the healthy subjects using the index. Significant changes were observed in the 5 indices reflecting the characteristics of coated tongue area, and the accuracy of the discriminant model constructed using these indicators was 67.9%.
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15:05-15:20, Paper FrCT13.4 | Add to My Program |
A Novel Pulse Waveform Analysis System for Radial Artery Pulse Diagnosis in Oriental Medicine (I) |
Jeon, Youngju | Korean Inst. of Oriental Medicine |
Kim, Young-Min | Korea Inst. of Oriental Medicine |
Kim, Jong Yeol | Korea Inst. of Oriental Medicine |
Kim, Jaeuk U | Korean Inst. of Oriental Medicine |
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15:20-15:35, Paper FrCT13.5 | Add to My Program |
Development of Phenotype Measurement and Analysis System for Constitution-Specific Treatment (I) |
Do, Jun-Hyeong | Korea Inst. of Oriental Medicine |
Jang, Jun-Su | Korea Inst. of Oriental Medicine |
Kim, Young-Min | Korea Inst. of Oriental Medicine |
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15:35-15:50, Paper FrCT13.6 | Add to My Program |
A Study on the Development of the Abdomen Diagnosis Devices Based on Korean Medicine for Functional Dyspepsia (I) |
Kim, Keun Ho | Korea Inst. of Oriental Medicine |
Lee, Sanghun | Korea Inst. of Oriental Medicine |
Keywords: Diagnostic devices - Physiological monitoring, Health technology - Verification and validation, Clinical engineering
Abstract: The purpose of this study is to develop a diagnostic device which simulates the abdomen diagnosis in Korean medicine and an algorithm to classify functional dyspepsia by using the device. Diagnostic factors include abdominal stiffness, pain position and sensitivity, body temperature distribution, repetitive tone, and abdominal pattern characteristics. Through the development of the abdominal diagnostic device, it will be possible to analyze the diseases that were difficult to diagnose objectively so far.
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FrCT14 Oral Session, Schaldach Room |
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Image Rendering and Enhancement |
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Chair: Lepore, Natasha | Univ. of Southern California / Children's Hospital Los Angeles |
Co-Chair: Kawai, Toshikazu | Osaka Inst. of Tech |
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14:20-14:35, Paper FrCT14.1 | Add to My Program |
An Enhanced Hybrid Tracking-Mosaicking Approach for Surgical View Expansion |
Takada, Chisato | Chiba Univ |
Afifi, Ahmed | Chiba Univ |
Suzuki, Toshiyuki | Chiba Univ |
Nakaguchi, Toshiya | Chiba Univ |
Keywords: Image enhancement, Image reconstruction and enhancement - Image synthesis
Abstract: The aim of this work is to overcome the narrow surgical field of view problem in minimally invasive surgery. We achieve this by combining multiple views of the camera-retractable trocar which can obtain surgical viewpoints different from laparoscopic view. However, the accuracy and time are essential factors in this process. Therefore, we tend to improve the accuracy of a hybrid tracking-mosaicking approach which can combine several views at high speed. Two improvements are presented and analyzed here. The first improvement utilizes two sharping methodologies to enhance the image quality. This enhancement, in turn, improves the interest point extraction process and increases the number of extracted points. In the second enhancement, the tracking accuracy is improved by applying a filtering methodology to select the set of valid flow vectors only. This process reduces the tracking error which may accumulate during tracking. The experimental evaluation, shows that these improvements enhance the final mosaicking accuracy and allows us to construct a more accurate expanded view.
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14:35-14:50, Paper FrCT14.2 | Add to My Program |
A Low-Dimensional Representation for Individual Head Geometries |
Miklody, Daniel | Tech. Univ. Berlin |
Bagdasarian, Milena Teresa | Tech. Univ. Berlin, Fraunhofer HHI |
Blankertz, Benjamin | Tech. Univ. Berlin |
Keywords: Image feature extraction, Brain image analysis, Electrical source imaging
Abstract: In the estimation of individual head geometries for source localization and electrical stimulation in neuroelectric investigations and application, mostly complex geometrical models are directly extracted from anatomical images. We present a novel method that uses a dimensionality reduction from thousands down to the range of tens of parameters to successfully represent an individual 4-shell Boundary Element Method (BEM) head model, which can successively be fitted to any kind of data from an individual head (e.g. headshape, impedances) and then used for individual head model creation. The results show, that around 15 -20 components can lead to satisfactory results.
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14:50-15:05, Paper FrCT14.3 | Add to My Program |
GPU-Based Volume Reconstruction for Freehand 3D Ultrasound Imaging |
Wen, Tiexiang | Shenzhen Inst. of Advanced Tech. Acad |
Liu, Lei | Shenzhen Inst. of Advanced Tech. Acad |
Qin, Wenjian | Shenzhen Inst. of Advanced Tech. Acad |
Gu, Jia | Shenzhen Inst. of Advanced Tech |
Keywords: Image reconstruction - Fast algorithms
Abstract: Volume reconstruction plays an important role in improving image quality for freehand three-dimensional (3D) ultrasound imaging. The kernel regression provides an effective method for volume reconstruction in 3D ultrasound imaging, but it requires heavily computational time-cost. In this paper, a programmable graphic-processor-unit- (GPU) based fast kernel regression method is proposed for freehand 3D ultrasound volume reconstruction. The most significant aspect of our method is the adopting of powerful data-parallel computing capability of GPU to improve the overall efficiency. To produce higher image quality, the results of the kernel regression with various parameter settings is deeply investigated under the help of the fast implementation of the algorithm. Experimental results demonstrate that the computational performance of the proposed GPU-based method can be over 200 times faster than that on CPU. Better image quality for speckle reduction and details preservation can be obtained with the parameter setting of kernel window size of 5×5×5 and kernel bandwidth of 1.0.
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15:05-15:20, Paper FrCT14.4 | Add to My Program |
BrainWatch Software for Interactive Exploration of Brain Scans in 3D Virtual Reality Systems |
Taswell, S. Koby | Brain Health Alliance |
Veeramacheneni, Teja | Brain Health Alliance |
Taswell, Carl | Brain Health Alliance |
Keywords: Volume rendering, Brain image analysis
Abstract: The ability to view medical images as 3D objects, which can be explored interactively, has now become possible due to the advent of rapidly emerging virtual reality (VR) technologies. In the past, VR has been used as an educational tool for learning anatomy, a visualization tool for assisting surgery, and a therapeutic tool for rehabilitating patients with motor disorders. However, these older systems were either expensive to build or difficult to acquire and use. Exploiting the arrival of new consumer devices such as the Oculus Rift that are now affordable, we have developed a software application called BrainWatch for VR ready computers to enable 3D visualization and interactive exploration of DICOM data sets focusing on PET and MRI brain scans. BrainWatch software provides a unique set of 3 approaches for interacting with the virtual object which we have named the observatory scenario with an external camera, the planetarium scenario with an internal camera, and the voyager scenario with a mobile camera. A live interactive demonstration of BrainWatch VR with the Oculus Rift CV1 will be available for conference attendees to experience at EMBC 2017.
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15:20-15:35, Paper FrCT14.5 | Add to My Program |
Image Recognition of Triangular Tissue of an Organ Pulled by Forceps in Surgical Working Area for Laparoscope Robot |
Nakasuji, Hisa | Osaka Inst. of Tech |
Naruki, Kazuki | Osaka Inst. of Tech |
Kawai, Toshikazu | Osaka Inst. of Tech |
Nishikawa, Atsushi | Shinshu Univ |
Nishizawa, Yuji | Department of Gastroenterological Surgery, Faculty of Medicine, |
Nakamura, Tatsuo | Kyoto Univ |
Keywords: Image reconstruction and enhancement - Image synthesis, Image visualization, Image feature extraction
Abstract: An image processing method using selected corner points and ridge lines to recognize triangular tissue of an organ pulled by forceps in a laparoscopic view has been developed. The proposed method could be used for semi-automatic control of a laparoscope robot. It makes use of a masking process based on the recognition of the forceps and clots, detection of corner points for a Delaunay diagram, detection of ridge lines oriented in the same direction, and recognition of the triangular working area. Triangles recognized in laparoscopic surgical videos using this method were similar to the correct triangles made by an endoscopic specialist.
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15:35-15:50, Paper FrCT14.6 | Add to My Program |
A Fast Forward Solver of Fluorescence Diffuse Optical Tomography Based on the Lattice Boltzmann Method |
Zhang, Wenqing | Shanghai Univ |
Yan, Zhuangzhi | Shanghai Univ |
jiang, jiehui | Shanghai Univ |
Keywords: Optical imaging, Multimodal molecular imaging, Optical imaging and microscopy - Diffuse optical tomography
Abstract: Fluorescence diffuse optical tomography (FDOT) is a new molecular imaging technology, which uses near-infrared light to excite the fluorophore in tissues. According to the measurements detected on the surface of imaged object, the fluorescent quantum yield as well as lifetime of the fluorescence can be reconstructed. However, the reconstruction of FDOT remains a challenging problem because the conventional forward solvers are time consuming. Thus, a forward model solver that would enable the fast imaging is necessary. This paper describes a new forward solver to simulate the propagation of photons in tissues based on the lattice Boltzmann method (LBM). This is accomplished by propagation photons in tissues guided by the LBM. To evaluate the performance of the proposed LBM, based on the numerical simulation, we compared the light distribution generated by the LBM with the diffusion equation implemented by COMSOL in four different cases. The experimental results indicate that compared to diffusion equation, the LBM can reduce the computation time for the forward solver of FDOT while preserving the similar accuracy.
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FrCT15 Oral Session, Webster Room |
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Medical Technology - Clinical Testing |
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Chair: Forner-Cordero, Arturo | Pol. School. Univ. of Sao Paulo |
Co-Chair: Joseph, Jayaraj | HTIC, Indian Inst. of Tech. Madras |
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14:20-14:35, Paper FrCT15.1 | Add to My Program |
Cardiac Safety Profile for Random Complex Waveforms |
Pratt, Hugh | CPLSO |
Andrews, Chris | Univ. of Queensland |
Panescu, Dorin | Advanced Cardiac Therapeutics |
Lake, Blossom | Shrewsbury and Telford Hospital |
Keywords: Medical technology - Safety, Medical technology - Design and development, Medical technology - Clinical testing/clinical trials
Abstract: Introduction: A rigorous method for assessing the Ventricular Fibrillation (VF) risk of a Random Complex Waveform (RCW) has not been previously available. Real-life hazardous events motivated us to develop such method. An RCW is observable and recordable. It consists of multiple different components randomly added one to the other. Assessment for VF risk exists for non-random waveforms, particularly VF thresholds for 50/60 Hz alternating currents, but not for RCWs. Methods: We developed a method which considers exposure to a segment of an RCW. It transforms complex segment exposure to values which can be compared with AC root-mean-square (rms) magnitude/duration curves, for determination of VF risk. Human contact could occur for any given time duration within the segment. The current of most risk is the greatest found for all possible instances of that duration. This is termed the “Probable Current” (PC) for that duration. All possible exposure durations in the waveform segment are considered, giving a set of PCs, thus allowing the plotting of a PC curve. The PC set is compared with a criterion for VF risk, termed the Justified Current (JC) curve. Results: The theory is presented. Demonstrations and examples are given. Code is shown for generating the PC curve. Conclusion: VF risk can be found for an RCW using the rigorous algorithm presented. Significance: The VF for RCWs has not been considered previously. A rigorous statement of a method for VF risk assessment allows extension from regular waveforms to RCWs. Keywords: Cardiac Risk, Fibrillation, Random Complex Waveform, Standards.
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14:35-14:50, Paper FrCT15.2 | Add to My Program |
Development of Respiratory Function Monitor for Neonates |
Takatori, Fumihiko | Nihon Kohden Corp |
Inoue, Shinichiro | NIHON KOHDEN Corp |
Togo, Satoru | Nihon Kohden Corp |
Yamamori, Shinji | Nihon Kohden Corp |
Keywords: Point of care - Respiratory monitoring, Medical technology - Design and development, Point of care - Detection and monitoring
Abstract: 10 million babies do not breathe immediately at birth. However, since they require only small tidal volume and easy to break lung. We developed respirator y function monitor which can monitor mask leak, expiratory tidal volume, respiratory rate, peak inspiratory pressure, and end-tidal CO2 at real time tracing. The neonatal flow sensor was specially designed and it integrate with small mainstream capnometer, cap-ONE. The tablet was used for display to enhance usability. The basic performance was confirmed using neonatal training test lung and it was easy to know leakage. The system might help newborn’s first breath safely.
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14:50-15:05, Paper FrCT15.3 | Add to My Program |
Transmission Delay Performance in Telemedicine: A Case Study |
Wang, Gang | Univ. of Connecticut |
Lin, Shan | Stony Brook Univ |
Mullen-Fortino, Margaret | Univ. of Pennsylvania |
Sokolsky, Oleg | Univ. of Pennsylvania |
Lee, Insup | Univ. of Pennsylvania |
Keywords: Information communication and networking - Wireless, Information communication and networking - e-Health, Information communication and networking - mHealth innovations
Abstract: Given the prevalence of chronic health conditions, such as diabetes, obesity, epilepsy, and cardiovascular diseases, telemedicine technologies are increasingly adopted to help patients better manage their care and treat these diseases at home. These emerging telemedicine systems have been deployed and tested in a number of different health programs and hospitals. However, due to the lack of dedicated and reliable networking infrastructure, achieving real-time data collection is a very challenging task. In this paper, we conduct a comprehensive analysis on the delay issues presented during the use of a store and forward telemonitoring system for congestive heart failure patients in urban Philadelphia. Results from this analysis reveal that 10.3% of the patient measurements experience delays of longer than 12 hours. Delays of up to several days occurred in 15.38% these patients who went on to be hospitalized. These delay issues exposed from urban scale real systems have a direct impact on the quality of remote health care, causing late diagnosis and intervention especially when patients are experiencing acute exacerbations. Our investigation results essentially call for regulations on telemedicine systems with an emphasis on their temporal constraints.
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15:05-15:20, Paper FrCT15.4 | Add to My Program |
A Novel Platform for Distributed and Remote Real-Time Monitoring of Animal Model Behavior in a Bioterium |
Manso, André | Insituto Superior Técnico, Univ. De Lisboa |
Martinho, Miguel | Inst. Superior Técnico, Univ. De Lisboa |
Plácido da Silva, Hugo | IST - Inst. Superior Técnico |
Silvério Cabrita, António | Coimbra Chemistry Center, Univ. of Coimbra |
Banganho, António Francisco | Inst. Pol. De Coimbra, ISEC |
Machado, Gonçalo | Isec |
Macedo, Milton | IPC - ISEC and LIBPhys |
Keywords: Medical technology - Clinical testing/clinical trials, Medical technology - Simulation, learning and training, Medical technology - Entrepreneurship and commercialization
Abstract: Animal models are an important resource in life sciences research; however, many of the procedures involving vivo models are complex and time consuming. A common problem while conducting experiments is observing the behavior of the models throughout their stay in the bioterium. Ideally, behavioral assessment should be frequent and rigorous, as a way of more accurately characterizing the animal model. However, to date, few suitable automated solutions can be found within the state-of-the-art. In this paper, we propose an autonomous platform for distributed behavioral data acquisition from individual animal habitats in bioteriums, with remote and online access to the data. This approach allows real-time observation of the status of the habitats, and retrieval of the logged data for post- processing. The work focuses on the use case of motion, temperature and water intake monitoring in small rodents, although the platform was designed to be general-purpose and extensible to other types of habitats and sensing configurations.
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15:20-15:35, Paper FrCT15.5 | Add to My Program |
Iquant™ Analyser : A Rapid Quantitative Immunoassay Reader |
Joseph, Jayaraj | HTIC, Indian Inst. of Tech. Madras |
Vasan, Jayaraman Kiruthi | Healthcare Tech. Innovation Center |
Shah, Malay Ilesh | Healthcare Tech. Innovation Center (HTIC), Indian Inst |
Sivaprakasam, Mohanasankar | Indian Inst. of Tech. Madras |
Mahajan, Lalit | J Mitra & Co Pvt. Ltd |
Keywords: Point of care - Diagnostics, Point of care - Technologies in resource limited settings, Medical technology - Design and development
Abstract: Lateral flow immunoassays (LFIA) used in rapid quantitative point of care testing require an accurate, reliable and easy to operate instrument to read the LFIA kit and calculate the quantitative result value. We present iQuant® Analyser, an immunoassay reader designed for reading the Quanti® range of LFIA test kits for key markers such as HbA1C, Vitamin D, TSH etc. The instrument utilizes a laser based confocal optics system to capture the test and control lines from the LFIA kit, digitizes the fluorescent signal with high spatiotemporal resolution, computes necessary peak area ratios, applies calibration curves and declares the final result in an automated manner with minimal operator input. The instrument uses kit specific calibration information embedded on each LFIA test kit, to compute the final clinical parameter without using any external calibration chip. An intuitive icon based interface enables easy operation with minimal key presses, suited for point of care applications. The technology is designed in a modular manner to enable the instrument to perform tests on various parameters such as HbA1C, TSH, and Vitamin D etc without any hardware changes, using test-specific LFIA kits. The functional performance of the iQuant Analyser was verified over the range of expected area ratio values with standard reference cartridges that provided stable fluorescent lines. Repeatability of the instrument was found to be excellent with coefficient of variation (CoV) of area ratios found to be less than 1%. The inter-instrument reproducibility was also found to be good with CoV less than 4 %. Tests using blood samples with Quanti LFIA kits verified the accuracy of HbA1C results to be acceptable as per international standards with errors < 4 %. The iQuant Analyser is a portable, easy to use rapid quantitative immunoassay reader best suited for point of care applications.
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15:35-15:50, Paper FrCT15.6 | Add to My Program |
An in Silico Method to Predict Net Calcium Transfer During Hemodialysis |
Maheshwari, Vaibhav | Renal Res. Inst |
Cherif, Alhaji | Renal Res. Inst |
Fuertinger, Doris | Renal Res. Inst |
Schappacher, Gudrun | Univ. of Graz |
Preciado, Priscila | Renal Res. Inst |
Thijssen, Stephan | Renal Res. Inst |
Bushinsky, David | Univ. of Rochester Medical Center |
Kotanko, Peter | Renal Res. Inst |
Keywords: Translational biomedical informatics - Knowledge modeling, Models of organs and medical devices - Inverse problems in biology, Systems biology and systems medicine - Modeling of biomolecular system dynamics
Abstract: International guidelines for chronic hemodialysis patients suggest a dialysate calcium concentration between 1.25 and 1.5 mmol/L. However, it is not certain if these dialysate calcium levels result in net calcium transfer into the patient. With ubiquitous prevalence of vascular calcification in hemodialysis patients, it is pertinent to model the mass balance of calcium during dialysis. To this end, we developed a two compartmental patient model and spatiotemporal representation of dialyzer model to investigate and quantify the calcium mass balance during dialysis. The model accounts for calcium-albumin binding and varying protein concentration; the latter accounts for the Gibbs-Donnan effect. The model simulations suggest that despite a lower dialysate calcium concentration of 1.25 mmol/L, some of our patients may be loaded with calcium during dialysis. This net calcium flux from dialysate to blood side may be a potential contributor to vascular calcification, a primary cause of cardiovascular mortality in hemodialysis patients.
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FrCT16 Minisymposium, Rushmer Room |
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Advanced Robotic Surgery Based on Deep Tissue Imaging and Haptic Feedback
Technology |
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Chair: Kim, Chulhong | Pohang Univ. of Science and Tech |
Co-Chair: chung, wankyun | Postech |
Organizer: Kim, Chulhong | Pohang Univ. of Science and Tech |
Organizer: chung, wankyun | Postech |
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14:20-14:35, Paper FrCT16.1 | Add to My Program |
Dermoscopy Guided Dark-Field Multi-Functional Optical Coherence Tomography (I) |
Kwon, Soonjae | POSTECH |
Yoon, Yeoreum | POSTECH |
Kim, Bumju | POSTECH |
Jang, Won Hyuk | POSTECH |
Oh, Byungho | Keimyung Univ. Coll. of Medicine |
Chung, Kee Yang | Severance Hospital, Cutaneous Biology Res. Inst |
Kim, Ki Hean | POSTECH |
Keywords: Optical imaging - Coherence tomography, Optical imaging, Optical imaging and microscopy - Optical vascular imaging
Abstract: Dermoscopy is a skin surface microscopic technique allowing specular reflection free observation of the skin, and has been used to examine pigmented skin lesions. However, dermoscopy has limitations in providing depth information due to lack of 3D resolution. In order to overcome the limitations, we developed dermoscopy guided multi-functional optical coherence tomography (MF-OCT) providing both high-contrast superficial information and depth-resolved structural, birefringent, and vascular information of the skin simultaneously. Dermoscopy and MF-OCT were combined by using a dichroic mirror, and dark-field configuration was adapted for MF-OCT to reduce specular reflection. After characterization, dermoscopy guided MF-OCT was applied to several human skin lesions such as the scar, port-wine stain (PWS) as well as the normal skin for demonstration. Various features of the scar and PWS were elucidated by both dermoscopy and MF-OCT. Dermoscopy guided MF-OCT may be useful for evaluation and treatment monitoring of skin lesions in clinical applications.
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14:35-14:50, Paper FrCT16.2 | Add to My Program |
In Vivo Vasculature Imaging with a Clinical Photoacoustic and Ultrasound Imaging System (I) |
Kim, Jeesu | POSTECH |
Park, Eunyeong | Pohang Univ. of Science and Tech. (POSTECH) |
Choi, Wonseok | Pohang Univ. of Science and Tech. (POSTECH) |
Kim, Chulhong | Pohang Univ. of Science and Tech |
Keywords: Optical imaging
Abstract: Photoacoustic imaging is a promising imaging modality for visualizing both functional and structural information of biological tissues. In this article, we demonstrate a clinical photoacoustic and ultrasound imaging system for clinical practices. We have successfully visualized blood vessels in a human forearm by acquiring in vivo photoacoustic images.
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14:50-15:05, Paper FrCT16.3 | Add to My Program |
Reconfigurable DRE Simulator Using Augmented Haptics (I) |
Talhan, Aishwari | Kyung Hee Univ |
Jeon, Seokhee | Kyung Hee Univ |
Keywords: Multimodal image fusion
Abstract: There are various types of prostate palpation simulator, i.e., physical, virtual, or hybrid simulators. However, there exists no such single prostate palpation simulator that augments all kinds of diseases and generates reconfigurable scenarios using a single end-effector. In this paper, we present a seven cell prototype of prostate palpation simulator with augmented haptic feedback, capable of generating various reconfigurable scenarios for several prostate diseases with a single end-effector.
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15:05-15:20, Paper FrCT16.4 | Add to My Program |
Dielectro-Optofluidic Lens for Dynamic Focusing of Biomedical Imaging Techniques (I) |
Kim, Wonkyoung | Pohang Univ. of Science and Tech. (POSTECH) |
Park, Sang Min | Pohang Univ. of Science and Tech. (POSTECH) |
An, Seonga | Pohang Univ. of Science and Tech. (POSTECH) |
Yoo, Jaewon | Pohang Univ. of Science and Tech. (POSTECH) |
Kim, Dong Sung | Pohang Univ. of Science and Tech. (POSTECH) |
Keywords: Optical imaging, Optical imaging and microscopy - Microscopy
Abstract: We present a novel active lens for adjusting the focus of biomedical imaging techniques. The active lens is based on a curved interface formed between two immiscible liquids with different refractive index to refract light path. An electric field is applied to one liquid to change the position and curvature of the liquid interface, and finally, to adjust the focal length. The developed active lens is integrated with a photoacoustic microscopy system, which is an emerging non-invasive imaging technique, and its focus is successfully adjusted. Further, to improve the response time, tuning range, and stability of the active lens, the liquid interface is pinned at a sharp corner and the densities of the liquids are matched. This work paves the new way toward future biomedical imaging techniques.
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FrCT17 Oral Session, Einthoven Hall |
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Signal Processing - Sleep Analysis |
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Chair: Garde, Ainara | Univ. of Twente |
Co-Chair: OH, TONG IN | Kyunghee Univ |
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14:20-14:35, Paper FrCT17.1 | Add to My Program |
Snore Sound Recognition: On Wavelets and Classifiers from Deep Nets to Kernels |
Qian, Kun | Tech. Univ. of Munich |
Janott, Christoph | Tech. Univ. of Munich |
Jun, Deng | Univ. of Passau |
Heiser, Clemens | Tech. Univ. of Munich |
Hohenhorst, Winfried | Alfried Krupp Krankenhaus |
Herzog, Michael | Carl-Thiem-Klinikum Cottbus |
Cummins, Nicholas | Univ. of Passau |
Schuller, Bjoern | Univ. of Passau |
Keywords: Time-frequency and time-scale analysis - Wavelets, Signal pattern classification, Data mining and processing - Pattern recognition
Abstract: In this paper, we present a comprehensive comparison of wavelet features for the classification of snore sounds. Wavelet features have proven to be efficient in our previous work; however, the benefits of wavelet transform energy (WTE) and wavelet packet transform energy (WPTE) features were not clearly established. In this study, we firstly present our updated snore sounds database, expanded from 24 patients (collected by one medical centre) to 40 patients (collected by three medical centres). We then study the effects of varying frame sizes and overlaps for extraction of the wavelet low-level descriptors, the effect of which have yet to be fully established. We also compare the performance of the WTE and WPTE features when fed into multiple classifiers, namely, Support Vector Machines (SVM), K-Nearest Neighbours, Linear Discriminant Analysis, Random Forests, Extreme Learning Machines, Kernel Extreme Learning Machines, Multilayer Perceptron, and Deep Neural Networks. Key results presented indicate that, when fed into a SVM, WTE outperforms WPTE (one-tailed z-test, p<0:002). Further, WPTE can achieve a significant improvement when trained by a k-nearest neighbours classifier (one-tailed z-test, p < 0:001).
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14:35-14:50, Paper FrCT17.2 | Add to My Program |
A Bayesian Neural Network Approach to Compare the Spectral Information from Nasal Pressure and Thermistor Airflow in the Automatic Sleep Apnea Severity Estimation |
Gutierrez, Gonzalo Cesar | Univ. of Valladolid |
de Frutos, Julio | Hospital Univ. Río Hortega De Valladolid |
Álvarez, Daniel | Univ. of Valladolid, CIF: Q4718001C |
Vaquerizo-Villar, Fernando | Biomedical Engineering Group, Univ. of Valladolid |
Barroso-García, Verónica | Biomedical Engineering Group, E.T.S.I. De Telecomunicación, Univ |
Crespo, Andrea | Hospital Univ. Rio Hortega, Valladolid |
del Campo, Félix | Hospital Del Río Hortega. Univ. De Valladolid |
Hornero, Roberto | Univ. of Valladolid |
Keywords: Neural networks and support vector machines in biosignal processing and classification, Signal pattern classification, Physiological systems modeling - Multivariate signal processing
Abstract: In the sleep apnea-hypopnea syndrome (SAHS) context, airflow signal plays a key role for the simplification of the diagnostic process. It is measured during the standard diagnostic test by the acquisition of two simultaneous sensors: a nasal prong pressure (NPP) and a thermistor (TH). The current study focuses on the comparison of the spectral content of airflow obtained from these to help in the automatic SAHS-severity estimation. The spectral analysis of 315 NPP and corresponding TH recordings is firstly proposed to characterize the conventional band of interest for SAHS (0.025-0.050 Hz.). A magnitude squared coherence analysis is also conducted to quantify possible differences in the frequency components of airflow from the two sensors. Then, a feature selection stage is implemented to assess the relevance and redundancy of the information extracted from the spectrum of NPP and TH airflow. Finally, a multiclass Bayesian multi-layer perceptron (BY-MLP) was used to perform an automatic estimation of SAHS severity (no-SAHS, mild, moderate, and severe), by the use of the selected spectral features from: airflow NPP alone, airflow TH alone, and both sensors jointly. The highest diagnostic performance was reached by BY-MLP only trained with NPP spectral features, reaching Cohen’s kappa = 0.498 in the overall four-class classification task. It also achieved 91.3%, 84.9%, and 83.3% of accuracy in the binary evaluation of the 3 apnea-hypopnea index cut-offs that define the four SAHS degrees (5, 15, and 30 events/hour). Our results suggest that TH sensor might be not necessary for SAHS severity estimation if an automatic comprehensive characterization approach is adopted to simplify the diagnostic process.
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14:50-15:05, Paper FrCT17.3 | Add to My Program |
Estimation of a Priori Probabilities of Sleep Stages: A Cycle-Based Approach |
Tataraidze, Alexander | Bauman Moscow State Tech. Univ |
Anishchenko, Lesya | BMSTU |
Korostovtseva, Lyudmila | Federal North-West Medical Res. Centre |
Bochkarev, Mikhail | Federal North-West Medical Res. Centre |
Sviryaev, Yurii | Sleep Lab. Federal Almazov Medical Res. Centre |
Ivashov, Sergey | Bauman Moscow State Tech. Univ |
Keywords: Data mining and processing - Pattern recognition, Data mining and processing in biosignals
Abstract: This paper presents a model for the estimation of a priori probabilities of sleep epoch classes based on the epoch location in a sleep cycle. These probabilities are used as additional features for sleep stage classification based on the analysis of respiratory effort. The model was validated with data of 685 subjects selected from the Sleep Heart Health Study dataset. The model improves a base algorithm by 8 percent points and demonstrates Cohen's kappa of 0.56 ± 0.12. Our results will contribute to the development of screening tools for unobtrusive sleep structure estimation.
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15:05-15:20, Paper FrCT17.4 | Add to My Program |
Comparing Two Insomnia Detection Models of Clinical Diagnostic Techniques |
Mulaffer, Lamana | Texas A&M Univ. at Qatar |
Shahin, Mostafa | Texas A&M Univ. at Qatar |
Glos, Martin | Charite-Univ. Berlin |
Penzel, Thomas | Charite Univ. Berlin |
Ahmed, Beena | Texas A&M Univ. at Qatar |
Keywords: Neural networks and support vector machines in biosignal processing and classification
Abstract: Sleep disorders are becoming increasingly prevalent in society. However most of the burgeoning research on automated sleep analysis has been in the realm of sleep stage classification with limited focus on accurately diagnosing these disorders. In this paper, we explore two different models to discriminate between control and insomnia patients using support vector machine (SVM) classifiers. We validated the models using data collected from 124 participants, 70 control and 54 with insomnia. The first model uses 57 features derived from two channels of EEG data and achieved an accuracy of 81%. The second model uses 15 features from each participant’s hypnogram and achieved an accuracy of 74%. The impetus behind using these two models is to follow the clinician’s diagnostic decision-making process where both the EEG signals and the hypnograms are used. These results demonstrate that there is potential for further experimentation and improvement of the predictive capability of the models to help in diagnosing sleep disorders like insomnia.
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15:20-15:35, Paper FrCT17.5 | Add to My Program |
Usefulness of Discrete Wavelet Transform in the Analysis of Oximetry Signals to Assist in Childhood Sleep Apnea-Hypopnea Syndrome Diagnosis |
Vaquerizo-Villar, Fernando | Biomedical Engineering Group, Univ. of Valladolid |
Álvarez, Daniel | Univ. of Valladolid, CIF: Q4718001C |
Gutierrez, Gonzalo Cesar | Univ. of Valladolid |
Barroso-García, Verónica | Biomedical Engineering Group, E.T.S.I. De Telecomunicación, Univ |
Kheirandish-Gozal, Leila | Section of Sleep Medicine, Department of Pediatrics, Pritzker Sc |
Crespo, Andrea | Hospital Univ. Rio Hortega, Valladolid |
del Campo, Félix | Hospital Del Río Hortega. Univ. De Valladolid |
Gozal, David | Section of Sleep Medicine, Department of Pediatrics, Pritzker Sc |
Hornero, Roberto | Univ. of Valladolid |
Keywords: Time-frequency and time-scale analysis - Wavelets, Physiological systems modeling - Signal processing in physiological systems, Signal pattern classification
Abstract: Sleep apnea hypopnea syndrome (SAHS) is a high prevalent respiratory disorder that may cause many negative consequences for the health and development of children. The gold standard for diagnosis is the overnight polysomnography (PSG), which is a high cost, complex, intrusive and time-demanding technique. To improve the early detection of pediatric SAHS, we propose to develop an automated analysis of the SpO2 signal from nocturnal oximetry. A database composed of 298 SpO2 recordings from children ranging from 0 to 13 years old was used for this purpose. Due to the abrupt changes caused by respiratory events in the SpO2 signal, our goal was to evaluate the diagnostic ability from SpO2 recordings by means of the discrete wavelet transform (DWT). In order to achieve this objective, we developed a signal processing approach divided in two main stages: (i) feature extraction, where features from the DWT detail coefficients were computed, and (ii) feature classification, where a logistic regression (LR) model was used to classify children into SAHS negative or SAHS positive. Our results showed that respiratory events introduced more variability in the SpO2 signals in two detail levels of the DWT: 0.024-0.049 Hz and 0.012-0.024 Hz. Moreover, the LR classifier achieved an 81.88% accuracy (79.10% sensitivity and 84.15% specificity) in an independent test set for a clinical cutoff point of 5 events/h. These results suggest that DWT may be a useful tool to analyze SpO2 recordings in the context of childhood SAHS.
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15:35-15:50, Paper FrCT17.6 | Add to My Program |
Detecting Obstructive Sleep Apnea in Children by Self-Affine Visualization of Oximetry |
Garde, Ainara | Univ. of Twente |
Kheirkhah Dehkordi, Parastoo | Univ. of British Columbia |
Petersen, Christian | British Columbia Children's Hospital |
Ansermino, J. Mark | British Columbia's Children's Hospital |
Dumont, Guy | Univ. of British Columbia |
Keywords: Physiological systems modeling - Signal processing in physiological systems, Nonlinear dynamic analysis - Biomedical signals, Signal pattern classification
Abstract: Obstructive sleep apnea (OSA), characterized by cessations of breathing during sleep due to upper airway collapse, can affect the healthy growth and development of children. The gold standard for OSA diagnosis, polysomnography (PSG), is expensive and resource intensive, resulting in long waiting lists to perform a PSG. Previously, we investigated the time-frequency analysis of blood oxygen saturation (SpO2) to screen for OSA. We used overnight pulse oximetry from 146 children, collected using a smartphone-based pulse oximeter (Phone Oximeter), simultaneously with standard PSG. Sleep technicians manually scored PSG and provided the average of apnea/hypoapnea events per hour (AHI). In this study, we proposed an alternative method for analyzing SpO2, in which a set of contracting transformations form a self-affine set with a 2D attractor, previously developed for qualitative visualization of the photoplethysmogram and electroencephalogram. We applied this technique to the overnight SpO2 signal from individual patients and extracted features based on the distribution of points (radius and angle) in the visualization. The cloud of points in children without OSA (NonOSA) was more confined than in children with OSA, which was reflected by more empty pixels (radius and angles). The maximum value, skewness and standard deviation of the distribution of points located at different radius and angles were significantly (Bonferroni corrected) higher in NonOSA compared to OSA children. To detect OSA defined at different levels (AHI5, AHI10 and AHI15), three multivariate logistic regression models were implemented using a stepwise feature selection and internally validated through bootstrapping. The models (AHI5, AHI10, AHI15), consisting of 3, 4 and 1 features respectively, provided a bootstrap-corrected AUC of 73%, 81%, 73%. Thus, applying this visualization to nocturnal SpO2 could yield both visual and quantitative information that might be useful for screening children for OSA.
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FrCT18 Invited Session, Montgomery Hall |
Add to My Program |
Biomedical Data Beyond Linear Correlation: Higher Order Statistics and
Non-Gaussianity, Non-Linearity and Multifractality |
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Chair: Yamamoto, Yoshiharu | The Univ. of Tokyo |
Co-Chair: Abry, Patrice | ENS Lyon, CNRS |
Organizer: Yamamoto, Yoshiharu | The Univ. of Tokyo |
Organizer: Abry, Patrice | ENS Lyon, CNRS |
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14:20-14:35, Paper FrCT18.1 | Add to My Program |
Stochastic Quantifiers of Behavioral Dynamics in Psychiatric Disorders (I) |
Nakamura, Toru | Osaka Univ |
Yamamoto, Yoshiharu | The Univ. of Tokyo |
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14:35-14:50, Paper FrCT18.2 | Add to My Program |
Long-Range Amplitude Correlations and Non-Gaussian Behavior of Heart Rate Variability (I) |
Kiyono, Ken | Osaka Univ |
Miki, Yuki | Osaka Univ |
Tsujimoto, Yutaka | Graduate School of Engineering Science, Osaka Univ |
Watanabe, Eiichi | Fujita Health Univ |
Hayano, Junichiro | Nagoya City Univ |
Yamamoto, Yoshiharu | The Univ. of Tokyo |
Nomura, Taishin | Osaka Univ |
Keywords: Time-frequency and time-scale analysis - Nonstationary processing, Nonlinear dynamic analysis - Biomedical signals, Time-frequency and time-scale analysis - Wavelets
Abstract: In this paper, we investigated long-range amplitude correlations of human heart rate variability (HRV). By analyzing bandpass-filtered HRV time series corresponding to high-frequency (HF; 0.15 to 0.4 Hz) and low-frequency (LF; 0.04 to 0.15 Hz) bands, it was shown that amplitude variability of HF and LF bands displayed non-Gaussianity and long-range correlations. Furthermore, through the cross-correlation analysis of the HRV HF-band and respiration amplitudes, we found the existence of the long-range cross-correlation in the cardiorespiratory system. Based on these findings, we discuss the physiological and medical significance of non-Gaussian HRV and long-range amplitude correlation.
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14:50-15:05, Paper FrCT18.3 | Add to My Program |
Feature Selection and Machine Learning Based Supervised Classification for Intrapartum Fetal Acidosis Early Detection (I) |
Abry, Patrice | ENS Lyon, CNRS |
Leonarduzzi, Roberto Fabio | Ec. Normale Superieure De Lyon |
Spilka, Jiri | Czech Tech. Univ. in Prague |
Doret, Muriel | Hospices Civils De Lyon Univ. Lyon I |
Keywords: Time-frequency and time-scale analysis - Wavelets, Nonlinear dynamic analysis - Biomedical signals
Abstract: Characterizing intrapartum Fetal Heart Rate (FHR) constitutes a significant public health stake, both for understanding mechanisms regulating heart rate in healthy subjects and for characterization of the fetus health status. It is notably critical for the early detection of fetal acidosis, that requires a fast and relevant real-time decision by the obstetrician in charge of the delivery. Numerous features from several domains (spectral, non Gaussian, fractal, multifractal, information theoretic, ...) have been proposed for its characterization. This wealth of features requires the use of adequate classification tecniques to combine the information they provide. Also, feature selection strategies need to be used to select the most relevant features in order to enhance clinical interpretability. It has recently been proposed to combine these two elements in the so-called sparse support vector machines, which show very promising outcomes, with high performances achieved through the use of only a few features.
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15:05-15:20, Paper FrCT18.4 | Add to My Program |
Multiscale Properties of Instantaneous Parasympathetic Activity in Severe Congestive Heart Failure: A Survivor vs Non-Survivor Study |
Valenza, Gaetano | Univ. of Pisa |
Wendt, Herwig | CNRS, Univ. of Toulouse |
Kiyono, Ken | Osaka Univ |
Hayano, Junichiro | Nagoya City Univ |
Watanabe, Eiichi | Fujita Health Univ |
Yamamoto, Yoshiharu | The Univ. of Tokyo |
Abry, Patrice | ENS Lyon, CNRS |
Barbieri, Riccardo | Pol. Di Milano |
Keywords: Nonlinear dynamic analysis - Biomedical signals, Physiological systems modeling - Signal processing in physiological systems, Signal pattern classification
Abstract: Multifractal analysis of cardiovascular variability series is an effective tool for the characterization of pathological states associated with congestive heart failure (CHF). Consequently, variations of heartbeat scaling properties have been associated with the dynamical balancing of nonlinear sympathetic/vagal activity. Nevertheless, whether vagal dynamics has multifractal properties yet alone is currently unknown. In this study, we answer to this question by conducting multifractal analysis through wavelet leader-based multiscale representations of instantaneous series of vagal activity as estimated from inhomogeneous point process models. Experimental tests were performed on data gathered from 57 CHF patients, aiming to investigate the automatic recognition accuracy in predicting survivor and non-survivor patients after a 4 years follow up. Results clearly indicate that, on both CHF groups, the instantaneous vagal activity displays power-law scaling for a large range of scales, from ≃ 0.5s to ≃ 100s. Using standard SVM algorithms, this information also allows for a prediction of mortality at a single-subject level with an accuracy of 72.72%.
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15:20-15:35, Paper FrCT18.5 | Add to My Program |
Validation of Instantaneous Bispectral High-Frequency Power of Heartbeat Dynamics As a Marker of Cardiac Vagal Activity |
Valenza, Gaetano | Univ. of Pisa |
Greco, Alberto | Univ. of Pisa |
Scilingo, Enzo Pasquale | Univ. of Pisa |
Barbieri, Riccardo | Pol. Di Milano |
Keywords: Nonlinear dynamic analysis - Biomedical signals, Nonlinear dynamic analysis - Volterra-Wiener models in physiological systems, Physiological systems modeling - Signal processing in physiological systems
Abstract: Nonlinear analysis has been advocated as a very powerful methodological framework to study physiological signals, particularly when applied to heartbeat dynamics. To this extent, estimation of high-frequency (0.15-0.40 Hz) power from bispectra of cardiovascular variability series has been engaged as a marker of nonlinear vagal activity. Nevertheless, a proper validation of this specific measure has not been yet performed. In this study, we estimate instantaneous, nonlinear bispectral indices during postural changes under sympathetic and parasympathetic nervous system blockade. The analysis was performed on data from 14 healthy subjects undergoing a control supine-to-upright routine where they were selectively administered either atropine or propanolol. Instantaneous bis- pectra were obtained through Laguerre-transformed, linear and nonlinear kernels of a Wiener-Volterra model applied to heartbeat dynamics, embedded into a recently proposed inhomogeneous point-process framework. Results demonstrate that the integration of bispectra accounting for nonlinear cardiovascular control dynamics within the high-frequency band provides potentially reliable markers of vagal activity.
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15:35-15:50, Paper FrCT18.6 | Add to My Program |
Spatially Regularized Multifractal Analysis for Fmri Data |
Ciuciu, Philippe | CEA |
Wendt, Herwig | CNRS, Univ. of Toulouse |
Combrexelle, Sébastien | IRIT, Univ. of Toulouse |
Abry, Patrice | ENS Lyon, CNRS |
Keywords: Time-frequency and time-scale analysis - Wavelets, Nonlinear dynamic analysis - Biomedical signals
Abstract: Scale-free dynamics is nowadays a massively used paradigm to model infraslow macroscopic brain activity. Multifractal analysis is becoming the standard tool to characterize scale-free dynamics. It is commonly used on various modalities of neuroimaging data to evaluate whether arrhythmic fluctuations in ongoing or evoked brain activity are related to pathologies (Alzheimer, epilepsy) or task performance. The success of multifractal analysis in neurosciences remains however so far contrasted: While it lead to relevant findings on M/EEG data, less clear impact was shown when applied to fMRI data. This is mostly due to their poor time resolution and very short duration as well as to the fact that analysis remains performed voxelwise. To take advantage of the large amount of voxels recorded jointly in fMRI, the present contribution proposes the use of a recently introduced Bayesian formalism for multifractal analysis, that regularizes the estimation of the multifractality parameter of a given voxel using information from neighbor voxels. The benefits of this regularized multifractal analysis are illustrated by comparison against classical multifractal analysis on fMRI data collected on one subject, at rest and during a working memory task: Though not yet statistically significant, increased multifractality is observed in task-negative and task-positive networks, respectively.
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FrDT1-01 Poster Session, Roentgen Hall |
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Neural Networks and Support Vector Machines in Biosignal Processing and
Classification |
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16:10-16:12, Paper FrDT1-01.1 | Add to My Program |
Comparison of Methods for Motor Imaginary Classification by Neural Network in a Single Channel BCI |
Iwata, Yuuki | Waseda Univ |
Ishiyama, Atsushi | Waseda Univ |
Keywords: Neural networks and support vector machines in biosignal processing and classification
Abstract: An electroencephalograph (EEG) was used to measure brain activity related to motor imaginary tasks pertaining to the right and left hands. Further, accuracy was calculated by deep-learning from the EEG signal at a single channel. Samples were transformed to 4-30 Hz frequencies by wavelet transformation, and a common spatial patterns (CSP) filter was prepared and adapted. For calculating accuracy, two methods were prepared, training by convolutional neural network (CNN) and training variance of filtered signals by a feedforward neural network (FFNN). In a result, the accuracy of FFNN is significantly higher than that of CNN and we applied weight decay to FFNN and selected best parameters that are more effective. It showed the possibility of enabling the training of a single channel EEG signal by separating frequencies and calculating variance from filtered CSP signals.
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16:12-16:14, Paper FrDT1-01.2 | Add to My Program |
Individualized Assessment of Cerebral Autoregulation in Patients with Intracranial Stenosis Using Machine Learning |
qiu, quanli | Chinese Acad. of Sciences, Shenzhen Inst. of Advanced Tec |
Zhang, Pandeng | Chinese Acad. of Sciences |
Liu, Jia | Chinese Acad. of Sciences |
Keywords: Neural networks and support vector machines in biosignal processing and classification
Abstract: In this study, we attempt to individualize the assessment of cerebral autoregulation in patients with intracranial stenosis. Convolution neural network (CNN) was applied to learn autoregulatory parameters estimated from healthy subjects and patients with severe stenosis with symptoms. We then used the trained model to individualize the status of autoregulation in the 5 groups of patients.
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16:14-16:16, Paper FrDT1-01.3 | Add to My Program |
Deception Detection Algorithm Based on K-PCA and SVM |
Jang, Yurim | Yonsei Univ |
Hwang, Layoung | Yonsei Univ |
Kim, Heesong | National Forensic Service |
Ji, Hyungki | National Forensic Service |
Hong, Hyeongi | National Forensic Service |
Kim, Kipyoung | National Forensic Service |
Pyo, Chuyun | National Forensic Service |
Shin, Taemin | Yonsei Univ |
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16:16-16:18, Paper FrDT1-01.4 | Add to My Program |
Detection of Game Craving in Young Individuals with Internet Gaming Addiction Using Multiple Biosignals |
Kim, Hodam | Hanyang Univ |
Ha, Jihyeon | Center for Bionics, Korea Inst. of Science and Tech |
Park, Wanjoo | KIST |
Kim, Laehyun | Korea Inst. of Science and Tech |
Im, Chang-Hwan | Hanyang Univ |
Keywords: Neural networks and support vector machines in biosignal processing and classification, Signal pattern classification
Abstract: Craving is an important factor for understanding addiction. In particular, classifying whether an individual is craving for something might be helpful in computer-aided treatments of addiction. In this study, we classified craving states of individuals with internet gaming addiction with a fairly high accuracy of 78.4%, using multiple biosignals, such as autonomic nervous responses and electrooculogram (EOG), recorded while video clips of highly addictive games were screening.
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FrDT1-02 Poster Session, Roentgen Hall |
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Signal Pattern Classification |
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16:10-16:12, Paper FrDT1-02.1 | Add to My Program |
A Method for Removing Effects of Electrode Impedance Imbalance and Muscle Fatigue on Hand Gesture Electromyogram Signals |
Jang, Seungwan | Daelim Univ |
Seo, Ahyeon | Daelim Univ |
Yang, Hansol | Daelim Univ |
Lee, Deuk Yong | Daelim Univ |
Yun, Yonghyeon | Daelim Univ. Coll |
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16:12-16:14, Paper FrDT1-02.2 | Add to My Program |
Pilot Study of Cardiotocography |
Zhayida, Simayijiang | Lund Univ |
Åström, Kalle | Lund Univ |
Källén, Karin | Lund Univ. Hospital |
Keywords: Signal pattern classification, Adaptive filtering
Abstract: A major problem in CTG analysis is that detection of a suspicious pattern in short intervals so that one can reduce the damage caused by a delay of an automatic monitoring system. In this paper, we aim for improving intrapartum surveillance based on signal processing and machine learning techniques. We evaluate a classification method on a real data set.
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16:14-16:16, Paper FrDT1-02.3 | Add to My Program |
Time-Varying Multivariate Risk-Stratification for Patients with Chronic Heart Failure |
O'Donnell, Johanna | Univ. of Oxford |
Velardo, Carmelo | Univ. of Oxford |
Khorshidi, Reza | Univ. of Oxford |
Rahimi, Kazem | Univ. of Oxford |
Tarassenko, Lionel | Univ. of Oxford |
Keywords: Signal pattern classification, Data mining and processing - Pattern recognition
Abstract: Heart failure (HF) is a chronic and prevalent condition associated with high mortality rates. Repeated-measurement risk-stratification may help identify patients at risk of deterioration early and improve their likelihood of survival. The aim of this research was to study the ability of well-established HF markers, including weight and New York Heart Association (NYHA) functional classification, to predict HF-related deterioration. Data from 58 heart failure patients were collected as part of the Support-HF study. Patients were asked to record daily weight readings and NYHA scores over a period of six months. Data were cleaned and weight, missing value and NYHA markers were extracted. The outcome to be predicted was seven-day HF deterioration, defined as sustained increases in NYHA. A random forest classifier was trained on a subset of 80% of the data and tested on the remaining 20%. Five-fold cross-validation was performed to accurately determine the performance of the classifier based on area under the curve scores. The combination of daily weight recordings, missing values and NYHA scores achieved moderate accuracy in predicting seven-day HF deterioration, defined as sustained increases in NYHA.
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16:16-16:18, Paper FrDT1-02.4 | Add to My Program |
Preliminary Study: Drowsiness Detection Using Non-Contact ITO Film Glasses |
Choi, Sangho | Seoul National Univ |
Lee, Jeongsu | Seoul National Univ |
Hong, Seunghyeok | Seoul National Univ |
Kwon, Hyunbin | Seoul National Univ |
Park, Kwang S. | Seoul National Univ |
Keywords: Signal pattern classification, Time-frequency and time-scale analysis - Time-frequency analysis
Abstract: Drowsiness during driving is a serious problem causing car accidents. Thus, the development of an effective drowsiness detection system is needed to reduce fatal crashes. In this study, we investigated the possibility of detecting drowsiness using non-contact indium tin oxide (ITO) film glasses. In order to measure drowsiness quantitatively, we used driving simulator. Five subjects participated in driving simulation wearing of ITO film glasses. After extracting peak related parameters from labeled data, LDA, KNN, and SVM algorithms were used to classify drowsiness. The best performance for detecting drowsiness was provided with a sensitivity 81.7%, a specificity of 82.7% and an accuracy of 91.8%.
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16:18-16:20, Paper FrDT1-02.5 | Add to My Program |
3-Phases of Cough Motor Act Analysis Using Accelerometer and Cough Sound |
KIM, Joo-Young | Hanyang Univ |
So, Soonwon | Hanyang Univ |
Yi, Ji Eun | Biomedical Engineering Department, Univ. of Hanyang |
Kim, In-Young | Hanyang Univ |
Keywords: Signal pattern classification
Abstract: Coughing is divided into three phases of motor act, which are inspiratory phase, compressive and expulsive phase. At this time, the conventional analysis of the cough motor act phase generally measures the cough sound, air flow, and esophageal pressure. This paper presents a new cough motor act phase analysis method using accelerometer and sound at abdomen.
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16:20-16:22, Paper FrDT1-02.6 | Add to My Program |
ECG Quality Classification Based on Similarity between Segments Simultaneously Measured from Different Electrodes |
Kim, Yoon Jae | Seoul National Univ |
Heo, Jeong | Seoul National Univ. Interdisciplinary Program for Bioengi |
Kim, Myungjoon | Interdisciplinary Program in Bioengineering, Seoul National Univ |
Park, Kwang S. | Seoul National Univ |
Kim, Sungwan | Seoul National Univ |
Keywords: Signal pattern classification, Data mining and processing in biosignals, Data mining and processing - Pattern recognition
Abstract: Non-constraint and non-intrusive measurement of ECG using electrodes embedded on smart wheelchair can provide various health parameters of the users. However, it seriously affected by motion artifact caused by human movement and oscillation. In this research, an approach to classify clean segment of ECG is suggested and validated. Two features which use standard deviation of RR interval and R peak amplitude were utilized. Furthermore, R peak locations were compared between ECG segments measured simultaneously. It enables segments with arrhythmia to be classified to clean segment even though their R peak is not stable. Five-fold cross validation results exhibited accuracy of 92.8%.
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16:22-16:24, Paper FrDT1-02.7 | Add to My Program |
Multimodal Hand Stereotypies Detection in Rett Syndrome Treatment Using Deep Belief Neural Networks |
O'Leary, Heather | Boston Children's Hospital |
Mayor Torres, Juan Manuel | Boston Children's Hospital |
D'Gama, Alissa | Harvard Medical School |
Kaufmann, Walter | Greenwood Genetic Center |
Sahin, Mustafa | Boston Children's Hospital |
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16:24-16:26, Paper FrDT1-02.8 | Add to My Program |
Vest Type Multiplexed Wearable Device for Cardiac Arrest Detection |
Ahn, Hyun Jun | Hanyang Univ |
Lee, hyojin | Biomedical Engineering Department, Univ. of Hanyang |
Lee, Junchang | Hanyang Univ |
Kim, In-Young | Hanyang Univ |
Keywords: Signal pattern classification
Abstract: Cardiac arrest is owing to the failure of the heart that makes the blood circulation stop. Arrested blood circulation prevents the supply of the oxygen and the glucose and it results the loss of consciousness and, finally, brain death. Many public institution installed the AED for emergency treatment, but, it is not efficient when the patient is alone or composed of IMU, ECG, PCG sensors. With this device, we measure the individual’s motion, electrocardiography, and heart sound. If the cardiac arrest is detected, the device make a warning horn, send an emergency message and transmit the signal for defibrillation.
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16:26-16:28, Paper FrDT1-02.9 | Add to My Program |
ECG Classification Using Deep Learning |
Huang, Shu-yi | Chung Yuan Christian Univ |
Chao, Yi-Ping | Chang Gung Univ |
Shyu, Liang-Yu | Chung Yuan Christian Univ |
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16:28-16:30, Paper FrDT1-02.10 | Add to My Program |
Motion Artifact Detection Using Cross-Correlation Pattern Analysis of HbO and HbR in Fnirs Signal |
Lee, Gihyoun | Daegu Gyeongbuk Inst. of Science and Tech |
Jin, SangHyeon | DGIST |
LEE, SEUNG HYUN | DGIST |
Jinung, An | Daegu Gyeongbuk Inst. of Science & Tech |
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16:30-16:32, Paper FrDT1-02.11 | Add to My Program |
3-D Signature Recognition Method by Orientation Correction of Inertial Sensor |
Kang, Shinil | Hanyang Univ |
YOU, SUNGMIN | Hanyang Univ |
Lee, Jong-Shill | Hanyang Univ |
Kim, In-Young | Hanyang Univ |
Keywords: Signal pattern classification
Abstract: In this paper, an inertial sensor-based user gesture recognition method to measure and analyze 3-D signature is presented implementing H-IMU (Hanyang Inertial Measurement Unit) we developed using a combination of gyroscope, accelerometer and magnetometer sensors. 3-D signature authentication identify gesture by drawing one’s handwritten signature in the air using an inertial sensor. In order to avoid the influence of the orientation of the sensor when signing in space, a velocity vector is obtained. By rotating the velocity vector on the principal axis through the rotation matrix, all of the velocity vectors pointing in different directions can be made in the same direction. As a result, the same result can be obtained without being influenced by the orientation of the sensor when signing on the space.
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16:32-16:34, Paper FrDT1-02.12 | Add to My Program |
Gait Authentication Using 3-Axis Accelerometer : Regardless of the Direction of Gait and Position of the Sensor |
Lee, SeungJae | Hanyang Univ |
Kang, Shinil | Hanyang Univ |
Lee, Jong-Shill | Hanyang Univ |
Kim, In-Young | Hanyang Univ |
Keywords: Signal pattern classification
Abstract: Recently, a behavioral biometric gait of the person has amount of studying the characteristics of gait using the IMU sensor. In this paper, 3-axis accelerometer data obtained from H-IMU(Hanyang Inertial Measurement Unit), which we developed using a combination of accelerometer, gyroscope and magnetometer sensors are measured on the left thigh. H-IMU on left thigh enables gait authentication regardless of orientation and placement. By using gravity and direction vector component, 3-axis accelerometer data are compensated for disorientation error and displacement error. This would bring smartphone gait authentication into reality in the near future.
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16:34-16:36, Paper FrDT1-02.13 | Add to My Program |
3D Space Signature Recognition with EMG Signals |
Joo, Seongsoo | Hanyang Univ |
Dohyun, Kim | Hanyang Univ |
Lee, Jong-Shill | Hanyang Univ |
Kim, In-Young | Hanyang Univ |
Keywords: Signal pattern classification
Abstract: In this paper, we propose a method of personal identification using signed data in space with 8channel Myo armband equipment. In the preprocessing process, the 'channel rotation' method is used for user's convenience so that the user does not have to worry about the wearing method.
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16:36-16:38, Paper FrDT1-02.14 | Add to My Program |
A Method for Signal Leakage Correction of Minimum Variance Beamformer Using a Padé Approximation |
Lim, Sanghyun | Korea Res. Inst. of Standards and Science (KRISS) and Un |
Kim, Kiwoong | Korea Res. Inst. of Standards and Science |
Keywords: Signal pattern classification, Parametric filtering and estimation
Abstract: The beamforming method is used to reconstruct underlying source signals from multi-channel sensor recordings in various applications. However, the reconstructed signals are easily distorted by the signal leakage from other sources that have temporal or spatial correlations with the target source signal. This situation is very common in human brain data, such as Electroencephalography and Magnetoencephalography. In the present study, we propose a novel signal leakage correction method that automatically identifies and corrects the leakage signal from the reconstructed signals. The method nonlinearly decomposes the reconstructed signals by using a Padé approximation and identify the leakage signal based on the idea that leaked signal has zero phase lag. We conducted a simulation study with three weakly correlated sources that are distributed on the cortical surface. The proposed method showed general improvements in the reconstruction quality and effectiveness in the noisy environment.
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16:38-16:40, Paper FrDT1-02.15 | Add to My Program |
Heart Rate Estimation from PPG Using Dictionary Learning |
Lee, Kwang Jin | Gwangju Inst. of Science and Tech. (GIST) |
Park, Chanki | Gwangju Inst. of Science and Tech |
Lee, Boreom | Gwangju Inst. of Science and Tech. (GIST) |
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16:40-16:42, Paper FrDT1-02.16 | Add to My Program |
Conversion of Lip Movements into Speech Using Gaussian Mixture Models |
Ra, Rina | Graduate School of System Informatics, Kobe Univ |
Aihara, Ryo | Graduate School of System Informatics, Kobe Univ |
Takiguchi, Tetsuya | Kobe Univ |
Ariki, Yasuo | Kobe Univ |
Keywords: Signal pattern classification
Abstract: This paper describes a novel lip-to-speech conversion method that converts voiceless lip movements into voiced utterances without recognizing text information. Inspired by a Gaussian Mixture Model (GMM)-based voice conversion method, a GMM is estimated from jointed lip-movements and audio features, and for test, an input lip-movements feature is converted to the audio feature using maximum likelihood (ML) estimation. The proposed method has been evaluated using large-vocabulary continuous utterances and experimental results show that our proposed method effectively estimates spectral envelopes and fundamental frequencies of audio speech from voiceless lip movements.
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16:42-16:44, Paper FrDT1-02.17 | Add to My Program |
Cardiac Risk Assessment Based on T-Wave Statistics from Holter ECG |
Shibui, Toyohito | Hosei Univ. Graduate School |
aihara, mitsuki | Hosei Univ. Graduate School |
Kinukawa, Yoshiki | Hosei Univ. Graduate School |
Yana, Kazuo | Hosei Univ |
Ichikawa, Tomohide | Fujita Health Univ |
Watanabe, Eiichi | Fujita Health Univ |
Yana, Kazuo | Hosei Univ |
Keywords: Signal pattern classification, Data mining and processing - Pattern recognition
Abstract: This paper proposes a method of efficient assessment of the cardiac risk based on the T-wave statistics obtained from long term Holter ECG recordings. T-wave alternans, T-wave amplitude variability and related indices are suggested to be utilized for the integrated cardiac risk assessment. The method has been applied to the Holter ECG data taken from 351 patients hospitalized at Fujita Health University Hospital due to acute coronary syndrome. It has been shown that TAVP could differentiate patients with ejection fraction < 40%.
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16:44-16:46, Paper FrDT1-02.18 | Add to My Program |
EEG Based Emotional State Tracking During Watching Movie Considering Self-Assessment Manikin |
Terasawa, Naoto | Nara Inst. of Science and Tech |
Tanaka, Hiroki | Nara Inst. of Science and Tech |
Sakriani, Sakti | Nara Inst. of Science and Tech |
Satoshi, Nakamura | Nara Inst. of Science and Tech |
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16:46-16:48, Paper FrDT1-02.19 | Add to My Program |
Improved Performance of Near-Infrared Spectroscopy Brain-Computer Interface Using Combinations of Multi-Distance Source-Detector Separations |
Shin, Jaeyoung | Hanyang Univ |
Kwon, Jinuk | Hanyang Univ |
Im, Chang-Hwan | Hanyang Univ |
Keywords: Signal pattern classification
Abstract: We attempted to improve performance of near-infrared spectroscopy (NIRS) brain-computer interface (BCI) in terms of a classification accuracy using combinations of multi-distance source-detector (SD) separations. So far, 30 mm source-detector separation has been generally used as a standard in NIRS measurements. Improved BCI performance (79.9 %) could be achieved by combining two sorts of SD separations among 15, 21.2, 30, and 33.5 mm, compared to the performance of conventional 30 mm SD separation (75.2 %).
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16:48-16:50, Paper FrDT1-02.20 | Add to My Program |
Classifying Modulation Waveforms of Visual Stimuli Via Steady-State Visual Evoked Potentials |
Tanji, Yutaro | Tokyo Univ. of Agriculture and Tech |
Morikawa, Naoki | Tokyo Univ. of Agriculture and Tech |
Nakanishi, Masaki | Univ. of California San Diego |
Suefusa, Kaori | Tokyo Univ. of Agriculture and Tech |
Tanaka, Toshihisa | Tokyo Univ. of Agriculture and Tech |
Keywords: Signal pattern classification
Abstract: In an steady-state visual evoked potential (SSVEP)-based brain--computer interface (BCI), visual stimulus design plays an important role to increase the number of commands. This paper introduces a new stimulation method that uses waveforms of visual stimuli for BCI commands. Experimental results showed that modulation waveform could be classified from elicited SSVEPs, which indicates the potential to increase the number of commands by embedding combined frequency and waveform information in visual stimuli.
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16:50-16:52, Paper FrDT1-02.21 | Add to My Program |
Prediction of Atrial Fibrillation Based on Random Forest Classifier |
Kim, Hyeonggon | Yonsei |
Kang, Chang Hoon | Yonsei Univ |
Myoung, Hyoun Seok | Yonsei Univ |
Lee, Seung Hwan | Yonsei Univ |
Lee, Kyoung Joung | Yonsei Univ |
Keywords: Signal pattern classification, Time-frequency and time-scale analysis - Time-frequency analysis, Nonlinear dynamic analysis - Biomedical signals
Abstract: This study proposes the prediction of atrial fibrillation algorithm for efficient and accurate diagnosis of patients with atrial fibrillation. We extracted three features from Poincare plot and Lorenz plot of δRR interval. Afterward, patients with atrial fibrillation and normal subjects are classified using Random Forest classifier. The classification result showed that sensitivity, specificity and accuracy were 81.82%, 95.24% and 87.04%. These results suggest that the performance is comparable to the previous atrial fibrillation algorithms.
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16:52-16:54, Paper FrDT1-02.22 | Add to My Program |
Cardiac Risk Assessment Based on Multiple Indices from Holter ECG Records |
Sato, Shunsuke | Hosei Univ |
murakami, mami | Hosei Univ. Graduate School |
Nakamura, Saya | Hosei Univ. Graduate School |
Yana, Kazuo | Hosei Univ |
Ono, Takuya | Nippon Medical School |
Yana, Kazuo | Hosei Univ |
Keywords: Signal pattern classification, Data mining and processing - Pattern recognition
Abstract: This paper examined the effectiveness of utilizing multiple indices based on the Holter ECG records for the cardiac risk assessment. Among several candidate indices, T-wave alternans ration percentile (TWAP) and RR interval amplitude (RRIA) showed prominent differences among different risk subject groups. Logistic regression with an additional index representing co-variability of RR and QT intervals yielded the average sensitivity of 0.817 and specificity 0.928 to differentiate three different risk classes.
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FrDT2 |
Cho Room |
Ignite Session F-02 |
Ignite Session |
Chair: Lee, Jong-Min | Hanyang Univ |
Co-Chair: Kim, Dong-Hyun | Yonsei Univ | |
16:10-16:20, Subsession FrDT2-01, Cho Room | |
Brain image analysis Poster Session, 5 papers |
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16:10-16:12, Subsession FrDT2-02, Cho Room | |
Magnetic resonance imaging - Contrast-enhanced dynamic MRI Poster Session, 1 paper |
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16:10-16:18, Subsession FrDT2-03, Cho Room | |
Magnetic resonance imaging - Diffusion tensor and diffusion spectrum imaging Poster Session, 4 papers |
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16:10-16:14, Subsession FrDT2-04, Cho Room | |
Magnetic resonance imaging - Image reconstruction Poster Session, 2 papers |
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16:10-16:28, Subsession FrDT2-06, Cho Room | |
Magnetic resonance imaging - MR neuroimaging Poster Session, 9 papers |
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16:10-16:18, Subsession FrDT2-07, Cho Room | |
Magnetic resonance imaging - MR spectroscopy Poster Session, 4 papers |
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16:10-16:12, Subsession FrDT2-08, Cho Room | |
Magnetic resonance imaging - MRI RF coil technology Poster Session, 1 paper |
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16:10-16:12, Subsession FrDT2-09, Cho Room | |
Magnetic resonance imaging - Pulse sequence Poster Session, 1 paper |
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FrDT2-01 Poster Session, Cho Room |
Add to My Program |
Brain Image Analysis |
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16:10-16:12, Paper FrDT2-01.1 | Add to My Program |
Arterial Spin Labeling in ASPECTS-Guided Machine Learning Can Predict Clinical Outcome in Acute Ischemic Stroke Patients |
Ma, Samantha J. | Univ. of Southern California |
Yu, Songlin | Beijing Tiantan Hospital, Capital Medical Univ |
Liebeskind, David S. | Univ. of California, Los Angeles |
Yan, Lirong | Univ. of Southern California |
Scalzo, Fabien | UCLA |
Wang, Danny JJ | Univ. of Southern California |
Keywords: Magnetic resonance imaging - MR neuroimaging, Brain image analysis
Abstract: The hemodynamic status following administration of thrombolytic therapies in acute ischemic stroke (AIS) is complex due to a variety of factors. Given the recent advancement in machine learning technology, perfusion patterns can be analyzed and used to understand potential clinical outcomes. This study utilizes a pattern recognition neural network model to predict modified Rankin Scale clinical outcome from Alberta Stroke Program Early CT Score (ASPECTS)-guided absolute cerebral blood flow (CBF) measurements. Considering the noise typically associated with arterial spin labeling, strategic machine learning enables improved interpretation of CBF data for AIS prognosis.
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16:12-16:14, Paper FrDT2-01.2 | Add to My Program |
MR Volume Registration Using Anatomical Reference Organ “Merkmal” for Analysis of the Brain Shift Transformation in the Closed Cranium |
Matsuda, Kento | Kobe Univ |
Kumamoto, Etsuko | Kobe Univ |
Hayashi, Shigeto | Hyogo Emergency Medical Center, Kobe Red Cross Hospital |
Nishino, Takashi | Department of Chemical Science and Engineering Faculty of Engine |
Nakai, Tomoaki | Department of Neurosurgery, Kobe Univ. Graduate School of M |
Kohmura, Eiji | Department of Neurosurgery, Kobe Univ. Graduate School of M |
Keywords: Brain image analysis, Deformable image registration, Magnetic resonance imaging - MR neuroimaging
Abstract: Brain shift transformation in the closed cranium is measured to analyze brain diseases with morphological defects. We proposed MR volume registration using the anatomical reference organ “Merkmal” that does not cause displacement and deformation due to posture changes. Obtained MR volume images of eight healthy volunteers demonstrated the effectiveness of our proposed method.
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16:14-16:16, Paper FrDT2-01.3 | Add to My Program |
Evaluating the Effect of Alzheimer's Disease Status on Co-Registration Accuracy of PET and MRI Brain Scans |
Veeramacheneni, Teja | Brain Health Alliance |
Taswell, S. Koby | Brain Health Alliance |
Taswell, Carl | Brain Health Alliance |
Keywords: Brain image analysis, Rigid-body image registration, Deformable image registration
Abstract: Does the clinical status of patients with either Alzheimer’s disease or mild cognitive impairment when compared with the normal healthy status of control subjects have an effect on the co-registration accuracy of the participants PET and MRI brain scans? An initial evaluation reveals that a statistically significant difference may exist in co-registration accuracy with some popular algorithms for the different groups of participants’ brain scans. These differences suggest that investigators should use appropriate caution when reviewing fusion studies of co-registered PET and MRI brain scans.
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16:16-16:18, Paper FrDT2-01.4 | Add to My Program |
Expanding Nexus Diristries of Dementia Literature with the NPDS Concept-Validating Search Engine Agent |
Bae, Seung-Ho | Brain Health Alliance |
Craig, Adam | Brain Health Alliance |
Taswell, Carl | Brain Health Alliance |
Keywords: General and theoretical informatics - Data mining, Health Informatics - Knowledge discovery and management
Abstract: Even though online databases make it easier than ever to access the biomedical and scientific literature about dementia, accelerating growth in the size of these databases has made it more difficult for humans to gather and analyze manually all articles relevant to any given topic. We document a Nexus-PORTAL-DOORS System (NPDS) Concept-Validating Search Engine Agent that can populate Nexus diristries with concept-validated metadata records for citations of journal articles found in literature databases.
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16:18-16:20, Paper FrDT2-01.5 | Add to My Program |
Quantitative Evaluation of Magnetic Nanoparticle Distribution in Murine Brain Using Magnetic Particle Imaging |
Inaoka, Yoshimi | Graduate School of Medicine, Osaka Univ |
Hosoi, Rie | Osaka Univ |
Murase, Kenya | Osaka Univ |
KIMURA, Astuomi | Osaka Univ |
Keywords: Brain image analysis
Abstract: We investigated the temporal change of the distribution of magnetic nanoparticles (MNPs) injected into murine striatum using magnetic particle imaging (MPI). Our results demonstrated that the behavior of MNPs in the brain differed depending on the environment surrounding the MNPs and suggest that MPI is useful for quantitatively evaluating the distribution of MNPs and its temporal change in the brain. Magnetic particle imaging (MPI) was introduced in 2005 as a new imaging modality, which allows imaging of the spatial distribution of magnetic nanoparticles (MNPs) with high sensitivity and spatial resolution . The tomographic image is reconstructed from MNP-derived signals whose intensities are linearly proportional to the amount of MNPs. In addition, the signal is not attenuated even if it is from deep inside the body. Cellular transplantation is studied as an effective treatment strategy for brain infarction and neurodegenerative diseases such as Parkinson disease. It is expected that MPI can be applied to mapping MNP-labeled cells in vivo for monitoring the efficacy of cellular transplantation. In this study, we performed animal experiments using 2 vectors, protamine and hemagglutinating virus of Japan-envelop (HVJ-E), to enhance the retention of MNPs. Each vector has a different mechanism to enhance the cellular uptake of MNPs. Protamine (positively-charged protein) helps the MNPs to adhere to cell surfaces by electrostatic interaction. HVJ-E, a novel non-viral vector, can envelop MNPs and directly introduce them into cells via cell membrane fusion .
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FrDT2-02 Poster Session, Cho Room |
Add to My Program |
Magnetic Resonance Imaging - Contrast-Enhanced Dynamic MRI |
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16:10-16:12, Paper FrDT2-02.1 | Add to My Program |
DCE-MRI Data Analysis with Simultaneous B1/T1 Estimation |
Zhang, Jin | NYU School of Medicine |
Winters, Kerry | NYU School of Medicine |
Kim, Gene | NYU School of Medicine |
Keywords: Magnetic resonance imaging - Contrast-enhanced dynamic MRI
Abstract: Dynamic contrast enhanced (DCE)-MRI data can be analyzed using a contrast kinetic model to estimate physiologically relevant parameters, such as transfer constant Ktrans, extracellular space volume fraction ve, and vascular space volume fraction vp. However, accurate estimation of these parameters requires RF-coil sensitivity (B 1) and pre-contrast longitudinal relaxation time (T 10). Active Contrast Encoding (ACE) -MRI has been proposed to estimate pharmacokinetic model parameters along with T 10 and B 1 from modified DCE-MRI data. In this study, we propose a novel, model-free approach to estimate T 10 and B 1 independently from estimation of contrast kinetic model parameters, while using the same ACE-MRI data, and demonstrate the technique in mouse model of brain tumor.
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FrDT2-03 Poster Session, Cho Room |
Add to My Program |
Magnetic Resonance Imaging - Diffusion Tensor and Diffusion Spectrum
Imaging |
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16:10-16:12, Paper FrDT2-03.1 | Add to My Program |
Correlation Tensor Using Resting State Fmri in Corpus Callosum |
Byeon, Kyoungseop | Sungkyunkwan Univ |
Lee, In Haeng | Sungkyunkwan Univ |
Lee, Dong Gyu | Sungkyunkwan Univ |
Kim, Jonghoon | Sung Kyun Kwan Univ |
Park, Bo-yong | Sungkyunkwan Univ |
Park, Hyunjin | Sungkyunkwan Univ |
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16:12-16:14, Paper FrDT2-03.2 | Add to My Program |
The Effects of Template and Improved Registration on Tract Based Spatial Statistics |
Choi, Yong-Ho | Hanyang Univ |
Kwon, Hunki | Department of Biomedical Engineering, Hanyang Univ |
Lee, Jong-Min | Hanyang Univ |
BOAHEN, COLLINS KWADWO | HANYANG Univ |
Keywords: Magnetic resonance imaging - Diffusion tensor and diffusion spectrum imaging, Brain image analysis
Abstract: Tract based spatial statistics (TBSS) has become a general pipeline for the analysis of white matter integrity of diffusion weighted imaging. However, several studies have reported some problems associated with TBSS pipeline. Recently, efforts have been made to improve such problems, especially, to use improved registration method or various atlas as target directly affect performance on the pipeline. We quantitatively evaluated the effect of both registration method and atlas on the performance.
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16:14-16:16, Paper FrDT2-03.3 | Add to My Program |
Bias-Free Fractional Anisotropy in Diffusion Tensor Imaging of the Brain Using a ROI Approach |
Seo, Youngseob | Korea Res. Inst. of Standards & Science (KRISS) |
Keywords: Magnetic resonance imaging - Diffusion tensor and diffusion spectrum imaging
Abstract: Clinical diffusion tensor imaging (DTI) is usually acquired with parallel imaging where the array coil offers improved SNR in the cortical areas of the brain but the SNR in the center of the brain remains relatively low. Low signal-to-noise ratio (SNR) can bias fractional anisotropy (FA). Particularly, regions with lower FA require higher SNR. Lower FA regions of the brain would require extensive signal average and this is not practical at 1.5 T. In this work we investigated manual region-of-interest (ROI)-based method for decreasing bias in FA measurement. The signals over the ROI were first averaged for raw images (b=0 image and diffusion weighted images with high b-values), and then the averaged values were used for estimating one diffusion tensor. A single observer manually placed ROIs on thalamus which is divided into ventral anterior (VA), lateral dorsal (LD) and ventral posterior (VP) nuclei, all having a low FA value. The bias for the ROI-based FA values was much less sensitive to NSA. FA bias using the ROI-based analysis was much smaller than that with pixel-based analysis.
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