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Last updated on July 25, 2018. This conference program is tentative and subject to change
Technical Program for Thursday July 19, 2018
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ThAT1 |
Meeting Room 311 |
Neural Signal Processing - I (Theme 6) |
Oral Session |
Chair: Sunderam, Sridhar | Univ. of Kentucky |
Co-Chair: Al-Jumaily, Adel | Univ. of Tech. Sydney |
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08:00-08:15, Paper ThAT1.1 | |
Single-Trial Detection of Semantic Anomalies from EEG During Listening to Spoken Sentences |
Tanaka, Hiroki | Nara Inst. of Science and Tech |
watanabe, hiroki | Nara Inst. of Science and Tech |
Maki, Hayato | Nara Inst. of Science and Tech |
Sakriani, Sakti | Nara Inst. of Science and Tech |
Satoshi, Nakamura | Nara Inst. of Science and Tech |
Keywords: Neural signal processing, Human performance, Human performance - Cognition
Abstract: We propose a method for the automatic detection of mismatched feelings that occur in communication. As our first step, we examined the semantically anomalous feelings from EEGs when participants listened to spoken sentences. Previous studies have shown that the event-related potentials (ERP) of an electroencephalogram (EEG) are evoked in the auditory and visual modalities where a semantic anomaly occurs. We expand this knowledge and detect it from a single-trial ERP using machine learning techniques. We recorded the brain activity of eight participants as they listened to sentences that contained semantic anomalies and found that a combination of feature selection using linear discriminant analysis and linear kernel support vector machines achieved the highest accuracy that exceeded 60%. By applying this technique, we plan to detect other types of anomalies in practical situations.
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08:15-08:30, Paper ThAT1.2 | |
Single Neuron Firing Rate Statistics in Motor Cortex During Execution and Observation of Movement |
Jiang, Xiyuan | Univ. of California, Los Angeles |
Ryu, Stephen | Stanford Univ |
Shenoy, Krishna V. | Stanford Univ |
Kao, Jonathan | Stanford Univ |
Keywords: Neural signal processing, Motor learning, neural control, and neuromuscular systems, Brain-computer/machine interface
Abstract: Mirror neurons, which fire during both the execution and observation of movement, are believed to play an important role in motor processing and learning. However, much work still remains to understand the similarities and differences in how these neurons compute in the motor cortex during movement execution and observation. Here, we performed experiments where a monkey both executes and observes a center-out-and-back task within the same experimental session. By recording from putatively the same neural population, we were able to analyze and compare single neuron statistics between movement execution and observation. We found that a majority of neurons in the primary motor cortex (M1) and dorsal premotor cortex (PMd) have statistically different firing rate statistics between movement execution and observation. As a result of this difference, we then wondered if neurons during movement observation exhibited a similar characteristic to those during movement execution: changing of preferred directions as a function of movement speed. Interestingly, we found that while observed movement speed is encoded in the neural population, it only alters a small proportion of the neuron’s firing rate statistics. These results suggest that neural populations in M1 and PMd process information related to movement differently between execution and observation.
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08:30-08:45, Paper ThAT1.3 | |
Individual Classification of Single Trial EEG Traces to Discriminate Brain Responses to Speech with Different Signal-To-Noise Ratios |
Fuentes Cabrera, Alvaro Rodrigo | UNEEG Medical |
Petersen, Eline Borch | Tech. Univ. of Denmark |
Graversen, Carina | Eriksholm Res. Centre |
Theil Sørensen, Allan | UNEEG Medical |
Lunner, Thomas | Eriksholm Res. Centre - Part of Oticon |
Rank, Mike Lind | Widex A/S |
Keywords: Neural signal processing, Human performance - Cognition
Abstract: To gain knowledge of listening effort in adverse situations, it is important to know how the brain processes speech with different signal-to-noise ratios (SNR). To investigate this, we conducted a study with 33 hearing impaired individuals, whose electroencephalographic (EEG) signals were recorded while listening to sentences presented in high and low levels of background noise. To discriminate between these two conditions, features from the 64-channel EEG recordings were extracted using the power spectrum obtained by a Fast Fourier Transform. Features vectors were selected on an individual basis by using the statistical R2 approach. The selected features were then classified by a Support Vector Machine with a non-linear kernel, and the classification results were validated using a leave-one-out strategy, and presented an average classification accuracy over all 33 subjects of 83% (SD=6.4%). The most discriminative features were selected in the high-beta (19–30 Hz) and gamma (30-45 Hz) bands. These results suggest that specific brain oscillations are involved in addressing background noise during speech stimuli, which may reflect differences in cognitive load between the conditions of low and high background noise.
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08:45-09:00, Paper ThAT1.4 | |
Effect of Vigilance Changes on the Incidence of High Frequency Oscillations in the Epileptic Brain |
Al-Bakri, Amir | Univ. of Kentucky |
Yaghouby, Farid | FDA |
Besio, W. G. | Univ. of Rhode Island |
Ding, Lei | Univ. of Oklahoma |
Modur, Pradeep | Univ. of Texas Southwestern Medical Center |
Sunderam, Sridhar | Univ. of Kentucky |
Keywords: Neural signal processing, Human performance - Sleep, Neurological disorders - Epilepsy
Abstract: Recent studies show that the rate of cortical high frequency oscillations (HFOs) differentiates epileptogenic tissue in individuals with epilepsy. However, HFO occurrence can vary widely with vigilance state. In this study we attempt to characterize this variation, which has implications for the choice of a suitable diagnostic baseline for spatiotemporal analysis of HFO activity. We analyzed simultaneous recordings of the scalp electroencephalogram (EEG) and the electrocorticogram (ECoG) to examine the correlation of HFO activity with vigilance state. We detected HFOs (80-500 Hz) from all bipolar ECoG derivations using the well-known Staba algorithm in ten seizure-free overnight recordings from five patients being evaluated for surgery. In addition, we classified EEG features using a linkage tree into four vigilance states representing gradations in sleep depth from wakefulness to slow wave sleep. Finally, we examined the correlation between vigilance state and HFO occurrence in the five channels with the most HFOs in each recording. The proportion of 30-s epochs containing HFOs was found to increase significantly with sleep depth (p < 0.01). Further analysis is necessary to examine the effects of epoch length and sample size in the choice of diagnostic baseline.
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09:00-09:15, Paper ThAT1.5 | |
Investigation of Propagating Cortical Waves and Spirals Recorded by High Density Porous Graphene Arrays |
Liu, Xin | Univ. of California San Diego |
Lu, Yichen | Univ. of California, San Diego |
Kuzum, Duygu | Univ. of California San Diego |
Keywords: Neural signal processing, Neural interfaces - Tissue-electrode interface, Neurological disorders - Epilepsy
Abstract: Propagating waves along the cortical surface have recently attracted significant attention by the neuroscience community. However, whether these propagating waves imply network connectivity changes for the neural circuits is not known. In this work, we employ a high density porous graphene microelectrode array and perform in vivo experiments with rodents to investigate network connectivity during cortical propagating waves. The spatial-temporal analysis of the cortical recordings reveals various types of propagating waves across the recording area. Network analysis results show that these propagating waves are consistent with the functional connectivity changes in the neural circuits, suggesting that the underlying network states are reflected by the cortical potential propagation patterns.
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09:15-09:30, Paper ThAT1.6 | |
A Deep Learning Approach for the Classification of Neuronal Cell Types |
Buccino, Alessio Paolo | Univ. of Oslo |
Ness, Torbjørn V | Norwegian Univ. of Life Sciences |
Einevoll, Gaute | Norwegian Univ. of Life Sciences |
Cauwenberghs, Gert | Univ. of California San Diego |
Häfliger, Philipp | Univ. of Oslo, Department of Informatics |
Keywords: Neural signal processing, Neural interfaces - Microelectrode technology, Brain physiology and modeling - Neuron modeling and simulation
Abstract: Classification of neurons from extracellular recordings is mainly limited to putatively excitatory or inhibitory units based on the spike shape and firing patterns. Narrow waveforms are considered to be fast spiking inhibitory neurons and broad waveforms excitatory neurons. The aim of this work is twofold. First, we intend to use the rich spatial information from high-density Multi-Electrode Arrays (MEAs) to make classification more robust; second, we hope to be able to classify sub-types of excitatory and inhibitory neurons. We first built, in simulation, a large dataset of action potentials from detailed neural models. Then, we extracted spike features from the simulated recordings on a high-density Multi-Electrode Array model. Finally, we used a Convolutional Neural Networks (CNN), to classify the different cell types. Compared with the ground truth data from the simulated dataset, the results show that this forward modelling/machine learning approach is very robust in recognizing excitatory and inhibitory spikes (accuracy ≥ 92.15 %). Additionally, the approach can, to a certain extent, correctly classify different cell sub-types. As the detail and fidelity of neural models increase and high-density recordings become available, this approach could become a viable and robust alternative for classification of neural cell types from in-vivo extracellular recordings.
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ThAT2 |
Meeting Room 312 |
Connectivity and Causality (Theme 1) |
Oral Session |
Chair: Mitsis, Georgios D. | McGill Univ |
Co-Chair: Valenza, Gaetano | Univ. of Pisa |
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08:00-08:15, Paper ThAT2.1 | |
Tracking of Dynamic Functional Connectivity from MEG Data with Kalman Filtering |
Tronarp, Filip | Aalto Univ |
Puthanmadam Subramaniyam, Narayan | Aalto Univ |
Särkkä, Simo | Aalto Univ |
Parkkonen, Lauri | Aalto Univ |
Keywords: Parametric filtering and estimation, Connectivity measurements, Kalman filtering
Abstract: Owing to their millisecond-scale temporal resolution, magnetoencephalography (MEG) and electroencephalography (EEG) are well-suited tools to study dynamic functional connectivity between regions in the human brain. However, current techniques to estimate functional connectivity from MEG/EEG are based on a two-step approach; first, the MEG/EEG inverse problem is solved to estimate the source activity, and second, connectivity is estimated between the sources. In this work, we propose a method for simultaneous estimation of source activities and their dynamic functional connectivity using a Kalman filter. Based on simulations, our approach can reliably estimate source activities and resolve their time-varying interactions even at low SNR (<1). When applied on empirical MEG responses to simple visual stimuli, our approach could capture the dynamic patterns of the underlying functional connectivity changes between the lower (pericalcarine) and higher (fusiform and parahippocampal) visual areas. In conclusion, we demonstrate that our approach is capable of tracking changes in functional connectivity at the millisecond resolution of MEG/EEG
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08:15-08:30, Paper ThAT2.2 | |
Does Independent Component Analysis Influence EEG Connectivity Analyses? |
Pester, Britta | Jena Univ. Hospital; Friedrich Schiller Univ. Jena |
Ligges, Carolin | Department of Child and Adolescent Psychiatry, Psychosomatic Med |
Keywords: Independent component analysis, Time-frequency and time-scale analysis - Time-frequency analysis
Abstract: Analysis of electroencephalographic (EEG) data requires cautious consideration of interfering artefacts such as ocular, muscular or cardiac noise. Independent component analysis (ICA) has proven to be a powerful tool for the detection and separation out of these contaminating components from brain activity. Yet thus far thorough investigation is lacking into how this pre-processing step might affect or even distort the information on brain connectivity inherent in the raw signals. The aim of this work is to address this question by systematically investigating and comparing three different strategies: first, analysis of all network nodes without eliminating contamination; second, removing the node which is contaminated by artefacts; third, using the ICA artefact removal method as an initial step prior to the analysis. Multivariate, time-variant autoregressive models are used to approximate the recorded data; the assessment of information flow within the modelled networks is carried out by means partial directed coherence, offering a frequency-selective estimation of connectivity.
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08:30-08:45, Paper ThAT2.3 | |
Increased Randomness of Functional Network Connectivity in Nicotine and Alcohol Consumers |
Vergara, Victor Manuel | The Mind Res. Network |
Hutchison, Kent | Univ. of Colorado Boulder |
Calhoun, Vince | The Mind Res. Network/Univ. of New Mexico |
Keywords: Physiological systems modeling - Multivariate signal processing, Connectivity measurements, Independent component analysis
Abstract: Alcohol and nicotine are substances that alter the functional connectivity of the brain. These changes have been observed after pinpointing particular brain areas as well as studying the overall brain wiring structure. One property of this wiring structure is the level of randomness. Evidence strongly agrees that brain connectivity is not random, but that chemical substances can affect the connectivity structure. This work aims at studying changes in resting state functional connectivity randomness in relation to the consumption of nicotine and alcohol. Results suggest that randomness in whole brain connectivity is not affected by used substance. However, connectivity among particular brain areas does show changed randomness linked to substance use. Abnormal randomness was found between salience and default mode functional domains. This dysfunction is in line with some postulates of the network model of addiction. The study provides new information on the effects of substance use on the brain.
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08:45-09:00, Paper ThAT2.4 | |
EEG Hyperconnectivity Study on Saxophone Quartet Playing in Ensemble |
Greco, Alberto | Univ. of Pisa |
Spada, Danilo | Univ. of Pavia, and Le2i, Univ. De Bourgogne Franche-C |
Rossi, Simone | Azienda Ospedaliera Univ. of Siena |
Perani, Daniela | Scientific Inst. San Raffaele, Milan |
Valenza, Gaetano | Univ. of Pisa |
Scilingo, Enzo Pasquale | Univ. of Pisa |
Keywords: Coupling and synchronization - Coherence in biomedical signal processing, Connectivity measurements, Physiological systems modeling - Signal processing in physiological systems
Abstract: A professional quartet of saxophonists playing in ensemble provides a perfect scenario to study the eventual occurrence of synchronous oscillatory brain activity across subjects. Here, we applied hyperscanning methodologies for simultaneously recordings of electroencephalographic (EEG) signals from four professional saxophonists while they observ an audiovideo recording of their own previous musical performance. An ad-hoc musical composition was written for the study. At debriefing, the subjects were asked to answer two questionnaires to assess their empathy trait and the musical leadership. In order to estimate the hyperconnectivity of each musician we proposed a measure which combines phase synchronization index of brain oscillations and graph theory framework. The inter-connectivity level of each musician was statistically compared. Statistical results revealed a significant lower hyperconnectivity in the left Brodmann area 44 for the Soprano with respect to the other three members. Recent theories attributed this brain region (Broca's area) to music generation, empathy processes and communication. We hypothesize a relationship between brain-to-brain connectivity level and the musical role within the quartet.
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09:00-09:15, Paper ThAT2.5 | |
Investigation of Interaction between Physiological Signals and Fmri Dynamic Functional Connectivity Using Independent Component Analysis |
Nikolaou, Foivia | Univ. of Cyprus |
Orphanidou, Christina | Univ. of Cyprus |
Murphy, Kevin | Cardiff Univ |
Wise, Richard G. | Cardiff Univ. Brain Res. Imaging Center (CUBRIC), Schoo |
Mitsis, Georgios D. | McGill Univ |
Keywords: Connectivity measurements, Independent component analysis, Signal pattern classification
Abstract: The blood oxygen level dependent (BOLD) fMRI signal is influenced not only by neuronal activity but also by fluctuations in physiological signals, including respiration, arterial CO2 and heart rate/ heart rate variability (HR/HRV). Even spontaneous physiological signal fluctuations have been shown to influence the BOLD fMRI signal in a regionally specific manner. Consequently, estimates of functional connectivity between different brain regions, performed when the subject is at rest, may be confounded by the effects of physiological signal fluctuations. In addition, resting functional connectivity has been shown to vary with respect to time (DFC), with the sources of this variation not fully elucidated. The effect of physiological factors on dynamic (time-varying) resting-state functional connectivity has not been studied extensively, to our knowledge. In our previous study, we investigated the effect of heart rate (HR) and end-tidal CO2 (PETCO2) on the time-varying network degree of three well-described RSNs (DMN, SMN and Visual Network) using mask-based and seed-based analysis, and we identified brain-heart interactions which were more pronounced in specific frequency bands. Here, we extend this work, by estimating DFC and its corresponding network degree for the RSNs, employing a data-driven approach to extract the RSNs (low- and high-dimensional Independent Component Analysis (ICA)), which we subsequently correlate with the characteristics of simultaneously collected physiological signals. The results confirm that physiological signals have a modulatory effect on resting-state, fMRI-based DFC.
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09:15-09:30, Paper ThAT2.6 | |
Identification of Time-Varying Cortico-Cortical and Cortico-Muscular Coherence During Motor Tasks with Multivariate Autoregressive Models |
Xifra-Porxas, Alba | McGill Univ |
Kostoglou, Kyriaki | McGill Univ |
Lariviere, Sara | McGill Univ |
Niso, Guiomar | McGill Univ |
Kassinopoulos, Michalis | McGill Univ |
Boudrias, Marie-Helene | McGill Univ |
Mitsis, Georgios D. | McGill Univ |
Keywords: Coupling and synchronization - Coherence in biomedical signal processing, Connectivity measurements, Time-frequency and time-scale analysis - Nonstationary processing
Abstract: Neural populations coordinate at fast sub-second time-scales during rest and task execution. As a result, functional brain connectivity assessed with different neuroimaging modalities (EEG, MEG, fMRI) may also change over different time scales. In addition to the more commonly used sliding window techniques, the General Linear Kalman Filter (GLFK) approach has been proposed to estimate time-varying brain connectivity. In the present work, we propose a modification of the GLFK approach to model time-varying connectivity. We also propose a systematic method to select the hyper-parameters of the model. We evaluate the performance of the method using MEG and EMG data collected from 12 young subjects performing two motor tasks (unimanual and bimanual hand grips), by quantifying time-varying cortico-cortical and cortico-muscular coherence (CCC and CMC). The CMC results revealed patterns in accordance with earlier findings, as well as an improvement in both time and frequency resolution compared to sliding window approaches. These results suggest that the proposed methodology is able to unveil accurate time-varying connectivity patterns with an excellent time resolution.
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ThAT3 |
Meeting Room 314 |
Brain Imaging: Connectivity and Networks (Theme 2) |
Oral Session |
Chair: Ji, Jim Xiuquan | Texas A&M Univ |
Co-Chair: Jarrahi, Behnaz | Stanford Univ. School of Medicine |
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08:00-08:15, Paper ThAT3.1 | |
Test-Retest Reliability of Functional Connectivity and Graph Metrics in the Resting Brain Network |
Jin, Dan | Univ. of Chinese Acad. of Sciences, Inst. of Automati |
Xu, Kaibin | National Lab. of Pattern Recognition, Inst. of Automat |
Liu, Bing | Inst. of Automation, Chinese Acad. of Sciences |
Jiang, Tianzi | Inst. of Automation |
Liu, Yong | Chinese Acad. of Sciences |
Keywords: Brain imaging and image analysis, Functional image analysis
Abstract: The combination of graph theoretical approaches and neuroimaging data provides a powerful way to explore the characteristics of brain network. Recently, the temporal variability of spontaneous brain activity and functional connectivity has attracted wide attention. Thus, it is essential to evaluate the reliability of functional network connectivity and properties from the dynamic perspective. However, previous test-retest (TRT) studies have explored this reliability with a static point of view. In this study, using a large rs-fMRI dataset from Human Connectome Project (HCP), we investigated TRT reliability of functional connectivity and graph metrics derived from the most commonly used method – sliding window at three time intervals (short: 72 seconds, middle: 15 minutes and long: >24 hours). The results revealed that reliable connectivities and related brain regions are mainly distributed in primary cortex, such as visual area and sensorimotor area and default mode network. Notably, connectivity strength and global efficiency have better reliability than other metrics. Finally, short scan time interval and long scan duration can increase the TRT reliability of metrics. Findings of present study provide important guidance for searching reliable network markers in future research.
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08:15-08:30, Paper ThAT3.2 | |
Implementation of High-Performance Correlation and Mapping Engine for Rapid Generation of Brain Connectivity Networks from Big Fmri Data |
Lusher, John | Texas A&M Univ |
Ji, Jim Xiuquan | Texas A&M Univ |
Keywords: Brain imaging and image analysis, Magnetic resonance imaging - MR neuroimaging, Functional image analysis
Abstract: With the emergence of the dynamic functional connectivity analysis, and the studies relying on real-time neurological feedback, the need for rapid processing methods becomes even more critical. Seed-based Correlation Analysis (SCA) of fMRI data has been used to create brain connectivity networks. With close to a million voxels in a fMRI dataset, the number of calculations involved in SCA becomes high. This work aims to demonstrate a new approach which produces high-resolution brain connectivity maps rapidly. The results show that HPCME with four FPGAs can improve the SCA processing speed by a factor of 40 or more over that of a PC workstation with a multicore CPU.
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08:30-08:45, Paper ThAT3.3 | |
Dynamic Influence of Ongoing Brain Stimulation on Resting State Fmri Connectivity: A Concurrent Tdcs-Fmri Study |
Wang, Xin | The Chinese Univ. of Hong Kong |
Wong, Wan-wa | The Chinese Univ. of Hong Kong |
FANG, Yuqi | Chinese Univ. of Hong Kong |
Chu, Winnie Chiu-wing | The Chinese Univ. of Hong Kong |
Tong, Kai Yu, Raymond | The Chinese Univ. of Hong Kong |
Keywords: Brain imaging and image analysis, Functional image analysis, Magnetic resonance imaging - MR neuroimaging
Abstract: Transcranial direct current stimulation (tDCS) is an emerging non-invasive neuromodulation technique that serves as treatment tool to neurological disorders. However, the mechanism of how the stimulation modulates ongoing brain activity and connectivity is still not fully understood. Simultaneous acquisition of neuroimaging data together with brain stimulation could allow a noninvasive examination of the brain dynamic changes during the process. In this pilot study, concurrent tDCS and fMRI was conducted in a healthy subject. Dynamic functional connectivity and effective connectivity were used to reveal the information flow. The results demonstrated that tDCS duration has important effects on the brain connectivity and the causal relationships among the brain regions. These results might reflect the fundamental mechanism of brain processing under the external stimulation.
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08:45-09:00, Paper ThAT3.4 | |
Characterizing the Effects of MR Image Quality Metrics on Intrinsic Connectivity Brain Networks: A Multivariate Approach |
Jarrahi, Behnaz | Stanford Univ |
Mackey, Sean | Stanford Univ. School of Medicine |
Keywords: Brain imaging and image analysis, Functional image analysis, Multivariate image analysis
Abstract: Motion-induced artifact detection has become a fixture in the assessment of functional magnetic resonance imaging (fMRI) quality control. However, the effects of other MR image quality (IQ) metrics on intrinsic connectivity brain networks are largely unexplored. Accordingly, we report herein the initial assessment of the effects of a comprehensive list of IQ metrics on resting state networks using a multivariate analysis of covariance (MANCOVA) approach based on high-order spatial independent component analysis (ICA). Three categories of MR IQ metrics were considered: (1) metrics for artifacts including the AFNI outlier ratio and quality index, framewise displacement, and ghost to signal ratio, (2) metrics for the temporal quality of MRI data including the temporal framewise change in global BOLD signals (DVARS), global correlation of time-series, and temporal signal to noise ratio, (3) metrics for the structural quality of MRI data including the entropy focus criterion, foreground-background energy ratio, full-width half maximum smoothness, and static signal to noise ratio. After FDR-correction for multiple comparisons, results showed significant effects of the static and temporal signal to noise ratios on the spatial map intensities of the basal ganglia, default-mode and cerebellar networks. AFNI outlier ratio, framewise displacement and DVARS exhibited significant effects on the BOLD power spectra of sensorimotor networks. The global correlation of time-series displayed wide-spread modulation of the spectral power in most networks. Further investigations of the effect of IQ metrics on the characteristics of intrinsic connectivity brain networks allow more accurate interpretation of the fMRI results.
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09:00-09:15, Paper ThAT3.5 | |
Measuring the Influence of Physiological Noise Corrections on ICA Derived Intrinsic Connectivity Brain Networks in Rest and Task Fmri |
Jarrahi, Behnaz | Stanford Univ |
Mackey, Sean | Stanford Univ. School of Medicine |
Keywords: Brain imaging and image analysis, Functional image analysis, Multivariate image analysis
Abstract: Physiological noise corrections using RETROICOR algorithm has been shown to increase signal sensitivity in resting state networks such as the default-mode network. However, independent component analysis (ICA)-based network approach may suffer from such corrections especially if there is any overlap between two sources in the decomposition domain. To address the extent the physiological noise corrections may impact ICA derived intrinsic connectivity brain networks, we measured network features including functional network connectivity (FNC), power spectra, and network spatial maps in the resting state and task functional magnetic resonance imaging (fMRI) data that were acquired in the same visit from a group of healthy volunteers. Statistical analysis showed functional connectivity between several networks were significantly changed after RETROICOR corrections in both rest and task fMRI. Significant FNC alterations were found in the subcortical, basal ganglia, salience, and default-mode networks. Power spectra analysis showed a trend toward lower power spectra in the subcortical and salience networks at [0.20 and 0.24] Hz after RETROICOR corrections in both rest and task fMRI. Furthermore, physiological noise corrections led to volumetric decrease in the resting state networks that included the subcortical, basal ganglia, salience, and default-mode networks, and volumetric enlargement in the sensorimotor and cerebellar networks. In task fMRI data, physiological noise corrections generally resulted in the expansion of networks except for task-activated networks including the anterior salience, central executive, dorsal attention, and cerebellar networks. If confirmed with larger sample sizes, these results suggest that physiological noise corrections alter some network features, and that such alterations are different between resting state and task fMRI data.
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09:15-09:30, Paper ThAT3.6 | |
Differential Amplitude of Low-Frequency Fluctuations in Brain Networks after BCI Training with and without Tdcs in Stroke |
Hu, Mengjiao | Nanyang Tech. Univ |
Keywords: Brain imaging and image analysis, Functional image analysis, Multimodal imaging
Abstract: Mapping the brain alterations post stroke and post intervention is important for rehabilitation therapy development. Previous work has shown changes in functional connectivity based on resting-state fMRI, structural connectivity derived from diffusion MRI and perfusion as a result of brain-computer interface-assisted motor imagery (MI-BCI) and transcranial direct current stimulation (tDCS) in upper-limb stroke rehabilitation. Besides functional connectivity, regional amplitude of local low-frequency fluctuations (ALFF) may provide complementary information on the underlying neural mechanism in disease. Yet, findings on spontaneous brain activity during resting-state in stroke patients after intervention are limited and inconsistent. Here, we sought to investigate the different brain alteration patterns induced by tDCS compared to MI-BCI for upper-limb rehabilitation in chronic stroke patients using resting-state fMRI-based ALFF method. Our results suggested that stroke patients have lower ALFF in the ipsilesional somatomotor network compared to controls at baseline. Increased ALFF at contralesional somatomotor network and alterations in higher-level cognitive networks such as the default mode network (DMN) and salience networks accompany motor recovery after intervention; though the MI-BCI alone group and MI-BCI combined with tDCS group exhibit differential patterns.
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ThAT4 |
Meeting Room 315 |
Minisymposia: New Challenges in Neurorehabilitation (31nvq) |
Minisymposium |
Chair: Chiappalone, Michela | Istituto Italiano Di Tecnologia |
Co-Chair: Semprini, Marianna | Italian Inst. of Tech |
Organizer: Chiappalone, Michela | Istituto Italiano Di Tecnologia |
Organizer: Semprini, Marianna | Italian Inst. of Tech |
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08:00-08:15, Paper ThAT4.1 | |
A Novel Lower Limb Exoskeleton and New Neurorehabilitation-Based Application Scenarios (I) |
Laffranchi, Matteo | Fondazione Istituto Italiano Di Tecnologia |
Semprini, Marianna | Italian Inst. of Tech |
Manzan, Emiliano | Fondazione Istituto Italiano Di Tecnologia |
Cerruti, Giulio | Fondazione Istuituto Italiano Di Tecnologia |
Vassallo, Christian | Fondazione Istituto Italiano Di Tecnologia |
De Giuseppe, Samuele | Fondazione Istituto Italiano Di Tecnologia |
Maludrottu, Stefano | Fondazione Istituto Italiano Di Tecnologia |
Succi, Antonio | Fondazione Istituto Italiano Di Tecnologia |
Chiappalone, Michela | Istituto Italiano Di Tecnologia |
Gruppioni, Emanuele | INAIL Centro Protesi Budrio |
De Michieli, Lorenzo | Fondazione Istituto Italiano Di Tecnologia |
Keywords: Neurorehabilitation, Neuromuscular systems - EMG processing and applications, Neural interfaces - Body interfaces
Abstract: Stroke, together with spinal cord injury (SCI), count up to 52% of the adult-onset disability. Enhancing the process of recovery of cognitive and motor functions after a neurological injury or disease is therefore widely recognized as a priority in healthcare. One of the opportunities in this direction lies in combining traditional approaches with robotic-based neurorehabilitation, thus improving the beneficial effects of the treatment. In this work, we present a novel exoskeleton device and propose its use in neurorehabilitation application scenarios.
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08:15-08:30, Paper ThAT4.2 | |
A Platform to Evaluate Cortical Changes Induced by Rehabilitation with Non-Invasive Brain Stimulation (I) |
Semprini, Marianna | Italian Inst. of Tech |
Bonassi, Gaia | Univ. Di Genova |
Pelosin, Elisa | Univ. Di Genova |
Mantini, Dante | ETH |
Avanzino, Laura | Univ. Di Genova |
Chiappalone, Michela | Istituto Italiano Di Tecnologia |
Keywords: Brain functional imaging - EEG, Neural stimulation, Neurorehabilitation
Abstract: We developed a platform for investigating the effect of non-invasive brain stimulation performed during cognitive rehabilitation. We integrated the system with high-density electroencephalography (hdEEG) recordings, which are processed with novel computational techniques providing accurate source localization. The platform allows the investigation of brain electrophysiological activity across the cognitive network during working memory tasks, in order to highlight the plastic changes, induced by the stimulation.
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08:30-08:45, Paper ThAT4.3 | |
Robotic Rehabilitation in Stroke and Parkinson’s Disease: Training Body Awareness to Improve Motor Function (I) |
Konczak, Juergen | Univ. of Minnesota |
Elangovan, Naveen | Univ. of Minnesota |
Yeh, I-Ling | Singapore Inst. of Tech |
Cuppone, Anna Vera | Istituto Italiano Di Tecnologia |
Keywords: Neurorehabilitation, Neurological disorders - Stroke, Neurological disorders - Treatment methodologies
Abstract: Cortical stroke or neurodegenerative diseases such as Parkinson’s disease can severely impair fine motor function of the hand. Restoration or preservation of this function is a major effort during neurorehabilitation. Many of these patients also exhibit proprioceptive deficits, which negatively impacts on motor re-learning. We here demonstrate that robotic rehabilitation approaches that aim to improve proprioceptive function can aid motor recovery or preserve sensorimotor function in neurodegenerative disease.
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08:45-09:00, Paper ThAT4.4 | |
Body Machine Interfaces for Assistance and Rehabilitation (I) |
Rizzoglio, Fabio | Univ. of Genoa |
Sciacchitano, Alessio | Univ. of Genoa |
Pierella, Camilla | École Pol. Fédérale De Lausanne |
Farshchiansadegh, Ali | Northwestern Univ |
Mussa-Ivaldi, Ferdinando | Northwestern Univ |
casadio, maura | Univ. of Genova |
Keywords: Motor learning, neural control, and neuromuscular systems, Neuromuscular systems - EMG processing and applications, Neurorehabilitation
Abstract: Body-machine interfaces (BMIs) are a viable option to control assistive devices and promote the recovery of movements after spinal cord injury, stroke or other neurological disorders that impair motor functions. BMIs translate signals from the body into the low dimensional control space of assistive and rehabilitative devices or of a personal computer. The mapping process allows us to select not only the subspace that is most comfortable for the user to act upon, but also the degrees of freedom and coordination patterns that the user has more difficulty engaging. Our goal is to develop BMI architectures that provide the user with the ability to identify and coordinate a convenient subset of movements and/or muscle signals for achieving task objectives with a flexible and adaptable motor behavior. Here we investigate methods to map muscle activities into control signals and to integrate activities from muscles and motion sensors to recover natural mobility.
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09:00-09:15, Paper ThAT4.5 | |
Non-Invasive Brain Stimulation to Enhance Neuro-Recovery and Rehabilitation (I) |
Harris-Love, Michelle | George Mason Univ |
Harrington, Rachael | George State Univ |
Chan, Evan (Chi-Pang) | MedStar Health Res. Inst |
Keywords: Neural stimulation, Neurorehabilitation, Neurological disorders - Stroke
Abstract: Non-invasive brain stimulation techniques, such as transcranial magnetic stimulation (TMS), can be used to both identify and manipulate recovery mechanisms post-stroke. In the latter case, non-invasive brain stimulation could be used as an adjuvant treatment that could enhance the efficacy of other rehabilitation therapies. The results of initial investigations into this possibility, however, have been largely inconclusive. There is a growing consensus that individual characteristics such as stroke location and severity are likely to be crucial considerations for identifying the stimulation parameters most likely to benefit recovery. To begin to address this, we studied the role of affected vs. unaffected hemisphere motor areas in movements of the paretic arm. We show that different motor areas contribute to paretic arm movements depending on the severity of corticospinal tract damage.
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ThAT5 |
Meeting Room 316A |
Minisymposia: Brain Computer Interface and Neurostimulation Technologies
for Paralysis and Limb Prosthetic Applications (tpi95) |
Minisymposium |
Chair: Bouton, Chad | Northwell Health/Feinstein Inst. for Medical Res |
Co-Chair: Gaunt, Robert | Univ. of Pittsburgh |
Organizer: Bouton, Chad | Northwell Health/Feinstein Inst. for Medical Res |
Organizer: Gaunt, Robert | Univ. of Pittsburgh |
Organizer: Coulter, Stewart | DEKA Res. and Development |
Organizer: Tyler, Dustin | Case Western Res. Univ |
|
08:00-08:15, Paper ThAT5.1 | |
Progress in Brain-Computer Interfaces for Restoring Movement and Sensation in Paralysis: What Have We Learned? (I) |
Bouton, Chad | Northwell Health/Feinstein Inst. for Medical Res |
Keywords: Brain-computer/machine interface, Neural interfaces - Implantable systems, Neural interfaces - Microelectrode technology
Abstract: Over the last two decades we have seen significant advances in brain-computer interfaces (BCI) and neurostimulation technologies. Paralyzed users have been able to feel tactile sensations and control computer cursors, robotic and prosthetic arms, and even move their own arms and hands through their own thoughts again, thanks to advances in the fields of BCI, robotics, and neuromuscular stimulation. Specifically, new results have been achieved recently in restoring functional, rhythmic, and graded hand movements in a human. Neural decoding methods and computer processing power have also improved, yet we still are challenged to understand how the brain encodes complex movements and how those modulation patterns change over time. New neural decoding methods and technologies such as ultra-high density brain and nerve interfaces are under development and will be key to advancing this field and providing clinically-relevant solutions to patients.
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08:15-08:30, Paper ThAT5.2 | |
Effects of Stimulus Frequency on Tactile Perception in a Long-Term Human Brain-Computer Interface (I) |
Gaunt, Robert | Univ. of Pittsburgh |
Hughes, Christopher | Univ. of Pittsburgh |
Flesher, Sharlene N | Stanford Univ |
Collinger, Jennifer | Univ. of Pittsburgh |
Boninger, Michael | Univ. of Pittsburgh |
Keywords: Sensory neuroprostheses - Somatosensory, Brain-computer/machine interface, Neural stimulation
Abstract: Intracortical microstimulation of the somatosensory cortex can be used to create a neuroprosthesis that restores tactile sensations even after long-term spinal cord injury. Evoked percepts have a range of qualities from pressure and touch, to tingling and buzzing, and an important area of investigation is to determine whether different stimulus parameters affect the perception of stimulation. Here we examine the effect of stimulus frequency and found that different electrodes produce more intense percepts in different frequency ranges and that these different groups of electrodes elicit sensations with different perceptual qualities.
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08:30-08:45, Paper ThAT5.3 | |
Peripheral Systems for Sensorimotor Restoration for Limb Prosthetics and Paralysis (I) |
Tyler, Dustin | Case Western Res. Univ |
Keywords: Sensory neuroprostheses, Neural interfaces - Implantable systems, Neural stimulation
Abstract: In Cleveland, peripheral nerve and intramuscular neurostimulation technologies have a nearly 50-year history of development and advancement to clinical implementation. Successful translation to chronic human implementation requires design that balances advanced technology, reliability, biocompatibility, and robustness. We present the current state of clinical peripheral nerve and intramuscular electrode technology in the context of sensorimotor restoration for limb prosthetics. We also present the iSens® neuromoduation system. iSens is a Bluetooth®-connected, modular system that can record or stimulate from up to 96 independent channels with real-time recording feature extraction; selectable bipolar electrode recording; multi-channel, asynchronous stimulation paradigms; and electrical field-shaping capability for improved nerve stimulation selectivity. We will present the results of implementation of latest clinical technology for more than five years in peripheral nerve stimulation for motor restoration in paralysis and sensory restoration and motor control in limb prosthetics. Finally, we discuss the technology capabilities of the iSens system and its potential as a platform for sensorimotor restoration.
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ThAT6 |
Meeting Room 316B |
Invited Session: Next Generation Neural Interfaces for Multimodal Recording
and Stimulation (1e91b) |
Invited Session |
Chair: Kuzum, Duygu | Univ. of California San Diego |
Co-Chair: Chamanzar, Maysamreza | Univ. of California Berkeley |
Organizer: Kuzum, Duygu | Univ. of California San Diego |
Organizer: Chamanzar, Maysamreza | Carnegie Mellon Univ |
|
08:00-08:15, Paper ThAT6.1 | |
Towards High Density Parylene Neural Probe Arrays for Large Scale Recording (I) |
Meng, Ellis | Univ. of Southern California |
Weltman Hirschberg, Ahuva | Univ. of Southern California |
Xu, Huijing | Univ. of Southern California |
Scholten, Kee | Univ. of Southern California |
Berger, Theodore | Univ. of Southern California |
Song, Dong | Univ. of Southern California |
Keywords: Neural interfaces - Bioelectric sensors
Abstract: Reliable chronic electrophysiological recordings remain elusive due to persistent biological failure affecting the electrode-tissue interface. We report on the development of conformal neural probe arrays microfabricated from thin film Parylene C. The use of a soft, flexible substrate seeks to minimize the immune response at interface and thereby improve the quality of chronic recordings. Acute implants of 64 electrode arrays were achieved and successfully targeted rat hippocampus. These technical advances seek to achieve high density arrays of polymer-based neural probes for chronic large scale recording of neural activity.
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08:15-08:30, Paper ThAT6.2 | |
Strategies for Large-Scale Optogenetics in Non-Human Primates (I) |
Yazdan-Shahmorad, Azadeh | Univ. of Washington |
Sabes, Philip N. | Univ. of California, San Francisco |
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08:30-08:45, Paper ThAT6.3 | |
Flexible Electronic/Optoelectronic Neural Interfaces (I) |
Rogers, John | Univ. of Illinois |
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08:45-09:00, Paper ThAT6.4 | |
Recent Advances in Neural Dust: Towards a Neural Interface Platform (I) |
Maharbiz, Michel | Univ. of California, Berkeley |
Keywords: Neural interfaces - Body interfaces
Abstract: Then neural dust platform uses ultrasonic power and communication to enable a scalable, wireless, and battery-less system for interfacing with the nervous system. Ultrasound offers several advantages over alternative wireless approaches, including a safe method for powering and communicating with sub mm-sized devices implanted deep in tissue. Our earlier studies demonstrated that neural dust motes could wirelessly transmit high-fidelity electrophysiological data in vivo, and that theoretically, this system could be miniaturized well below the mm-scale. I will review current work focused on further minimization of the platform, better encapsulation methods as a path towards truly chronic neural interfaces, improved delivery mechanisms, demonstration of in vivo stimulation capabilities, and modifications to the system that enable deployment of neural dust in the central nervous system.
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ThAT7 |
Meeting Room 316C |
Invited Session: Fostering Healthcare Transformation through Wearable
Sensors and Big Data at Work: Preventive, Pervasive and Personalized
Care. (35viy) |
Invited Session |
Chair: Seoane, Fernando | Karolinska Inst |
Co-Chair: Forsman, Mikael | Karolinska Inst |
Organizer: Seoane, Fernando | Karolinska Inst |
Organizer: Lindecrantz, Kaj | Royal Inst. of Tech |
|
08:00-08:15, Paper ThAT7.1 | |
Smart Textiles Enabling Sustainable Health at Work (I) |
Lindecrantz, Kaj | Royal Inst. of Tech |
Diaz-Olivares, Jose Antonio | Royal Inst. of Tech. (KTH) |
Abtahi, Farhad | KTH Royal Inst. of Tech |
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|
08:15-08:30, Paper ThAT7.2 | |
Wearable Sensors Enabling Personalized Occupational Healthcare (I) |
Abtahi, Farhad | KTH Royal Inst. of Tech |
Diaz-Olivares, Jose Antonio | Royal Inst. of Tech. (KTH) |
Lu, Ke | School of Tech. and Health, KTH Royal Inst. of Tech |
Forsman, Mikael | Karolinska Inst |
Lindecrantz, Kaj | Royal Inst. of Tech |
Keywords: Wearable sensor systems - User centered design and applications, Wearable body sensor networks and telemetric systems, Smart textiles and clothings
Abstract: The aim of this paper is to present the need and potential for wearable sensors in occupational healthcare. In addition, it partially presents ongoing European and Swedish projects for developing personalized, and pervasive wearable systems for assessing the risk of developing musculoskeletal disorders and cardiovascular diseases at work. Occupational healthcare might benefit by preventing the diseases and disorders by providing the right feedback at the right time to the right person. Collected data from workers can provide evidence supporting the ergonomic and industrial tasks of redesigning the working environment to reduce the risks.
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08:30-08:45, Paper ThAT7.3 | |
We@Work: Wellbeing, Health and Safety at Work (I) |
Seoane, Fernando | Karolinska Inst |
Mediavilla Martinez, César | Atos Spain S.A |
Diaz-Olivares, Jose Antonio | Royal Inst. of Tech. (KTH) |
Abtahi, Farhad | KTH Royal Inst. of Tech |
Keywords: Smart textiles and clothings, Wearable sensor systems - User centered design and applications, Integrated sensor systems
Abstract: Care cost for rehabilitation and treatment of work-related injuries and disorders are steadily increasing. Developments in sensing technologies, information and communication technologies allow for the development of novel p-health solutions for accurate assessment of risk exposure enabling prompt intervention for avoiding injuries. Combining sensorized garments, wearable electronics, mobile devices, cloud computing and machine learning, the We@work project has implemented an integral solution for preventive care of workers fostering a healthy and safe working life.
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08:45-09:00, Paper ThAT7.4 | |
Mobile Applications to Enhance Self-Healthcare and Wellbeing at Work (I) |
Rodríguez, Juan Mario | Atos Spain |
Aso, Santiago | Atos Spain, S.A |
Cavero Barca, Carlos | Atos Spain |
Vega-Barbas, Mario | Karolinska Inst |
Quintero, Ana María | Atos Spain |
Ramos Maia Martins, Ivo | Atos Spain |
Perez, Manuel | Athos Origin SA |
Mediavilla Martinez, César | Atos Spain S.A |
Jordan Rodriguez, Blanca | ATOS, Madrid |
Keywords: Modeling and analysis
Abstract: Pocket mHealth, a patient-centered solution owned by ATOS, enables patient empowerment in the management of its own medical information, storing their Electronic Health Record (EHR) and health data coming from different Hospital Information Systems (HIS). Pocket mHealth solves the need of current healthcare organizations into the adoption of healthcare data openness that following a patient centered design, taking advantage of the potential benefits of this paradigm. Instead of having standardized repositories at the hospital facilities, the patient becomes the driver of the change bringing standardized pieces of EHR in the mobile, what we call “distributed interoperability”.
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09:00-09:15, Paper ThAT7.5 | |
Prevention of Work-Related Ill-Health (I) |
Lind, Carl | Inst. of Environmental Medicine, Karolinska Inst. & Uni |
Eklund, Jörgen | KTH Royal Inst. of Tech. Unit of Ergonomics |
Yang, Liyun | KTH, Royal Inst. of Tech |
Forsman, Mikael | Karolinska Inst |
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09:15-09:30, Paper ThAT7.6 | |
The Need for Practical and Reliable Risk Assessment Methods for Prevention of Musculoskeletal Disorders (I) |
Forsman, Mikael | Karolinska Inst |
Yang, Liyun | KTH, Royal Inst. of Tech |
Borgström, Dennis | Karolinska Inst |
Lind, Carl | Inst. of Environmental Medicine, Karolinska Inst. & Uni |
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ThAT8 |
Meeting Room 318A |
Invited Session: Imaging Photoplethysmography and Remote Physiological
Sensing (3cg25) |
Invited Session |
Chair: Blackford, Ethan Brian | Ball Aerospace |
Co-Chair: McDuff, Daniel Jonathan | Microsoft |
Organizer: Blackford, Ethan Brian | Ball Aerospace |
Organizer: McDuff, Daniel Jonathan | Microsoft |
Organizer: Estepp, Justin Ronald | Air Force Res. Lab |
|
08:00-08:15, Paper ThAT8.1 | |
Spectral Estimation Methods for Evaluating Ippg Pulse Rate Variability |
McDuff, Daniel Jonathan | Massachusetts Inst. of Tech |
Blackford, Ethan Brian | Ball Aerospace |
Estepp, Justin Ronald | Air Force Res. Lab |
Keywords: Physiological monitoring - Modeling and analysis, Optical and photonic sensors and systems
Abstract: Non-contact measurement of physiological parameters, like pulse rate variability (PRV), has numerous applications in medicine and affective computing. PRV is an informative measure of autonomic nervous system activity. Spectral estimation from unevenly sampled, non-stationary data is integral to pulse rate variability frequency-domain analysis. We present the first comparison of results of PRV computation using the Lomb-Scargle method and Bayesian Spectral Estimation. The Lomb-Scargle method performs well, even in the presence of missing beats. However, the Bayesian Spectral Estimation method has advantages when tracking changes in amplitude and frequency. We illustrate these characteristics with results from synthetic data and real non-contact imaging photoplethysmography measurements.
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08:15-08:30, Paper ThAT8.2 | |
On the Invariance of Remote SpO2 Measurements to the Pulsating Profile of the Skin in the Red-Infrared Diagnostic Window (I) |
Moco, Andreia | Eindhoven Univ. of Tech |
Keywords: Infra-red imaging, Image feature extraction, Novel imaging modalities
Abstract: Remote pulse oximetry (SpO2) measurements are based on photons remitted from the skin. As photon path-lengths are influenced by wavelength and depth-dependent skin properties, the SpO2 calibration may be susceptible to the skin’s pulsating profile; i.e., to relative variations of arteriolar pulsations at upper-to-lower dermal layers. We hypothesize that preferring red-infrared wavelengths ensures similar penetration depths and invariance to pulsatile variations. We show diffuse reflectance measurements and Monte Carlo simulations of the normal and compressed skin, which support that photoplethysmographic (PPG) signals in red-infrared originate mostly from the deep vasculature. Complementarily, we use a skin model and assess, numerically, the accuracy of the ratio-of-ratios (RR) method for estimating SpO2 under pulsatile profiles within estimated realistic ranges. We consider the RRs between red (R; 660 nm) and infrared (IR; 840 nm) and the 80-100% SpO2 range. Our results indicate the invariance of remote SpO2 to the skin’s pulsating profile in R and IR.
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08:30-08:45, Paper ThAT8.3 | |
Assessment of Autonomic Response through Processing of Imaging Photo-Plethysmographic Signals in Psychophysiological Elicitation (I) |
Mainardi, Luca | Pol. Di Milano |
Iozzia, Luca | Pol. of Milan |
Valenza, Gaetano | Univ. of Pisa |
Cerina, Luca | Pol. of Milan |
Alberti, Chiara | Pol. Di Milano |
Eleonora, Centanini | Pol. Di Milano |
Colella, Angela | Pol. Di Milano |
Barbieri, Riccardo | Pol. Di Milano |
Keywords: Image analysis and classification - Machine learning / Deep learning approaches
Abstract: We investigated the ability of features extracted from noncontact Photo-Pletismography (PPG) signals in assessing Autonomic Nervous System (ANS) responses elicited by two sympathetic stimulations: i) rest-to-stand and ii) cold pressure tests. We observed that spectral parameters of Heart Rate Variability (HRV), obtained by post-processing of noncontact PPG, are able to highlight the expected parasympathetic withdrawal induced by the stimulations
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08:45-09:00, Paper ThAT8.4 | |
Noncontact PPG Monitoring from the Patient’s Back During Dental Treatment (I) |
Teichmann, Daniel | RWTH Aachen Univ |
Teichmann, Maren | RWTH Aachen Univ |
Hoog Antink, Christoph | RWTH Aachen Univ. Aachen, Germany |
Wolfart, Stefan | Univ. Hospital RWTH Univ |
Leonhardt, Steffen | RWTH Aachen Univ |
Walter, Marian | RWTH Aachen Univ |
Keywords: Optical imaging, Infra-red imaging
Abstract: This paper presents first results of a clinical study in which we tested reflective PPG sensors, which are integrated behind the fabric of a dentist chair’s backrest at three different locations, during dental treatment. Such sensors are able to measure through the fabric and the patient’s clothing. The system shows good results even during treatment phases where mechanical vibrations to the patient's body are induced, i.e. tooth cleaning with an ultrasonic scaler.
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09:00-09:15, Paper ThAT8.5 | |
High-Speed Multispectral Imaging Photoplethysmography (I) |
Blackford, Ethan Brian | Ball Aerospace |
Estepp, Justin Ronald | Air Force Res. Lab |
McDuff, Daniel Jonathan | Massachusetts Inst. of Tech |
Keywords: Optical imaging, Infra-red imaging, Optical imaging and microscopy - Optical vascular imaging
Abstract: Remote assessment of vital, cardiovascular system parameters presents numerous opportunities in the areas of health, human machine interfaces, and affective computing. Imaging photoplethysmography (iPPG), utilizing cameras to measure light absorption changes corresponding with the cardiac cycle is one such promising method for remote physiological assessment. Previous work has demonstrated improvements resulting from optimizing hardware designs and signal processing using the spectral relationship of the measured blood volume pulse signal. To further understanding and methods in this area, we recently developed a multispectral iPPG testbed with a comprehensive array of conventional color cameras, multispectral camera array, and synchronized reference physiological measurement. We present the finalized testbed and study design and preliminary results from the study consisting of seven trials intended to affect sensor measurements similarly to as expected in real-world settings or participant physiological, cognitive, or affective states
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ThAT9 |
Meeting Room 318B |
Invited Session: Bio-Sensing in Application Environment (27t73) |
Invited Session |
Chair: Lei, Kin Fong | Chang Gung Univ |
Co-Chair: Yao, Da-Jeng | National Tsing Hua Univ |
Organizer: Lei, Kin Fong | Chang Gung Univ |
Organizer: Yao, Da-Jeng | National Tsing Hua Univ |
|
08:00-08:15, Paper ThAT9.1 | |
Microengineered Systems to Modulate the Fusion of Cancer Cells (I) |
Sun, Yubing | UMass-Amherst |
Peyton, Shelly | Univ. of Massachusetts Amherst |
Zhu, Peiran | Univ. of Massachusetts Amherst |
Tseng, Ning-Hsuan | Univ. of Massachusetts Amherst |
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08:15-08:30, Paper ThAT9.2 | |
Quantitative Assessment for the Regularity of Activity of Daily Living (ADL) Using MEMS-Based Accelerometers and Its Potential Applications in Medical-Care (I) |
VERMA, VIJAY KUMAR | CHANG GUNG Univ |
Lin, Wen-Yen | Chang Gung Univ |
Lee, Ming-Yih | Chang Gung Univ |
Keywords: Micro- and nano-sensors, Micro- and nano-technology
Abstract: In this study, a quantitative assessment method for evaluating the regularity of activity of daily living (ADL) has been proposed based on the previously reported activity index (AI) from the MEMS-based accelerometer wrist-worn device. With 24 hours’ continuously measured AI, an hourly AI pattern for that day can be generated and by finding the correlation coefficient between this hourly AI pattern and the previous day’s pattern, the regularity index (RI) of ADL can be quantitatively assessed. RI provides quantified numbers for the regularity of daily life and can be used in activity-based evaluation models for many medical-care applications, such as the risk assessment and readmission prediction for COPD patients.
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08:30-08:45, Paper ThAT9.3 | |
Quantitative Assessment of the Growth of Tumor Spheroids (I) |
Huang, Chun-Hao | Chang Gung Univ |
Lei, Kin Fong | Chang Gung Univ |
Keywords: Micro- and nano-sensors, Microfluidic applications, Microfluidic techniques, methods and systems
Abstract: Tumor spheroid assay is generally used for the study of the development of early tumor and the effect of cytotoxic agents on tumors. In the current work, quantitative assessment of the growth of tumor spheroids was developed based on the impedance measurement technique. Result revealed that the impedance change could describe the growth of tumor spheroids during the culture. The technique owns the operation simplicity and quantitative assessment of tumor spheroids.
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08:45-09:00, Paper ThAT9.4 | |
Fertilization on a Chip (I) |
Huang, Yao-Huien | National Tsing Hua Univ |
Lai, Yun-Li | National Tsing Hua Univ |
Yao, Da-Jeng | National Tsing Hua Univ |
Keywords: Microfluidic applications, Microfluidic techniques, methods and systems, Micro- and nano-sensors
Abstract: In this presentation, EWOD (Electro-wetting on dielectric) system is used to be a dynamic culture platform for embryo formation until the status of BC (Blastocyst). The EWOD device is anticipated to provide a stable culture environment and improve the growth environment of mouse embryos based on its advantages of uniform hormone mixing in the culture medium. The development rate of embryos cultured by dynamic process is better than the one by static culture group. Other than digital microfluidic system, the continued microfluidic system will also be designed and used for insemination by sperms and oocyte and embryo culture. Either of microfluidic system would be used in clinical in the near future.
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09:00-09:15, Paper ThAT9.5 | |
Whole-Cell Biosensing System for Detecting Organic Toxicants in Food (I) |
Kao, Wei-Chen | Acad. Sinica Taiwan |
Belkin, Shimshon | Hebrew Univ. of Jerusalem |
Cheng, Ji-Yen | Acad. Sinica Taiwan |
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ThAT10 |
Meeting Room 319A |
Invited Session: Simulation of Neurological Disorders and Their Treatment
with Neuromodulation (49pq6) |
Invited Session |
Chair: Dokos, Socrates | Univ. of New South Wales |
Co-Chair: Shils, Jay | Rush Univ. Medical Center |
Organizer: Dokos, Socrates | Univ. of New South Wales |
Organizer: Shils, Jay | Rush Univ. Medical Center |
|
08:00-08:15, Paper ThAT10.1 | |
Neural Systems Modeling As Related to Intra-Operative Neuromonitoring (I) |
Shils, Jay | Rush Univ. Medical Center |
Mei, Longzhi | BIDMC |
Carlson, Kris | BIDMC |
Arle, Jeffrey | Beth Israel Deaconess Medical Center |
Keywords: Computational modeling - Biological networks, Model building - Network modeling, Models of organ physiology
Abstract: Motor evoked potentials are a commonly used monitoring methodology during surgeries that can put the motor system components at risk. Application of current to the motor tracts in the brain, via transcranial electrical stimulation, activates axons in the cortical spinal tract at different areas and affects the alpha motor neurons in the spine based on various stimulation parameters. Computational modeling has been used to show the likely location in the brain of stimulation activation as well as the optimal parameters for transmission of the signal through the corticospinal tract and within the spinal cord.
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08:15-08:30, Paper ThAT10.2 | |
Computational Modelling of Retinal Electrical Stimulation (I) |
Dokos, Socrates | Univ. of New South Wales |
Guo, Tianruo | Univ. of New South Wales |
Lovell, Nigel H. | Univ. of New South Wales |
Keywords: Modeling of cell, tissue, and regenerative medicine - 2d and 3d cell modeling, Data-driven modeling
Abstract: Improvements in the efficacy of retinal neuroprostheses can stem from investigating more sophisticated neural stimulation strategies which enable selective activation of specific retinal ganglion cells (RGCs). Computational models are particularly well suited for these investigations. The electric field can be accurately described by mathematical formalisms, and the neurons can be ‘probed’ at resolutions well beyond those achievable by today’s state-of-the-art biological techniques. In this study, we used computational models to explore the ability of high frequency electrical stimulation (HFS) to differentially activate ON and OFF RGCs. Performance of a wide range of electrical stimulation amplitudes and frequencies on functional RGC responses were evaluated.
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08:30-08:45, Paper ThAT10.3 | |
Computational Modeling Insights into Mechanisms of Action in Ultra High Frequency Spinal Cord Stimulation (I) |
Arle, Jeffrey | Beth Israel Deaconess Medical Center |
Carlson, Kris | BIDMC/Harvard Medical School |
Mei, Longzhi | BIDMC |
Shils, Jay | Rush Univ. Medical Center |
Keywords: Systems modeling - Clinical applications of biological networks, Model building - Algorithms and techniques for systems modeling, Models of medical devices
Abstract: The mechanisms of action in ultra high frequency (10kHz) dorsal column stimulation for pain remain unclear. There are generally two hypotheses: direct effects of the stimulation field on the dorsal horn or indirect effects via dorsal column axons on dorsal horn processing. While there is limited support for either hypothesis experimentally, prior computational efforts from our lab show the potential for differential suppression and stimulation of axon diameters in the dorsal column, in favor of the indirect hypothesis. We provide more support using bipolar biphasic stimuli with characteristics similar to what is used clinically, in multiple axonal membrane models and with detailed ionic channel simulations to show these findings are plausible.
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08:45-09:00, Paper ThAT10.4 | |
Advancements from Multi-Scale Modeling and Computational Trials for Gliomas (I) |
Fathallah-Shaykh, Hassan | UAB |
Keywords: Computational modeling - Analysis of high-throughput systems biology data, Systems modeling - Clinical applications of biological networks, Systems modeling - Decision making
Abstract: Gliomas are associated with poor outcome and significant neurological morbidity. Key biological features of these malignant brain tumors include mitosis, brain invasion, and angiogenesis (new blood vessel formation). Mathematical modeling of has made important contributions to the biology and clinical care of gliomas. The equations model the growth of grades 2-4 gliomas at the scales of pathology and magnetic resonance imaging; simulations yield computational trials (in silico clinical trials) that accurately predict the survival times of GBM patients. The results identify the rates of angiogenesis, migration, and replication as fundamental properties that predict survival times, response to treatment, and advancement to higher grades. The findings also uncover novel clinical behaviors, like evolution to higher grade, inability to transform, and new recurrence patterns of GBM treated by anti-angiogenic therapy. These results support the recent announcement by the Food and Drug Administration to use modeling and simulations in predicting effectiveness and clinical outcomes.
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09:00-09:15, Paper ThAT10.5 | |
Simulation: A Critical Ingredient in the Electroceutical Paradigm (I) |
Carlson, Kris | BIDMC/Harvard Medical School |
Mei, Longzhi | BIDMC |
Shils, Jay | Rush Univ. Medical Center |
Arle, Jeffrey | Beth Israel Deaconess Medical Center |
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09:15-09:30, Paper ThAT10.6 | |
Comparing Neuron Models with Compound Action Potential Measurements of Dorsal Column Axons (I) |
Parker, John | Saluda Medical Pty Ltd |
Laird-Wah, James | Saluda Medical |
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ThAT11 |
Meeting Room 319B |
Invited Session: The Role and Importance of Neuromechanics During Human
Locomotion (6ur75) |
Invited Session |
Chair: Ludvig, Daniel | Northwestern Univ |
Co-Chair: Rouse, Elliott | Univ. of Michigan |
Organizer: Ludvig, Daniel | Northwestern Univ |
Organizer: Rouse, Elliott | Univ. of Michigan |
|
08:00-08:15, Paper ThAT11.1 | |
The Confounding Effect of Continuously Varying Kinematics and Kinetics on Ankle Stiffness and Viscosity (I) |
Ludvig, Daniel | Northwestern Univ |
Whitmore, Mariah | Northwestern Univ |
Hargrove, Levi | Rehabilitation Inst. of Chicago |
Perreault, Eric | Northwestern Univ |
Keywords: Neuromuscular systems - Locomotion, Neuromuscular systems - Peripheral mechanisms, Neuromuscular systems - Computational modeling
Abstract: The mechanical impedance of our ankles plays a significant role in human locomotion. Recent studies have begun to characterize ankle impedance during movement tasks. However, it is difficult to determine how impedance varies with position, torque and muscle activation under the dynamic conditions of movement, as all three variables vary continuously. In this study we systematically investigated how dynamically varying position, torque and their interaction affect ankle impedance. We found that impedance during dynamic changes in either position or torque is much different than that estimated at matched isometric position and torques. However, most interesting was that dynamically and simultaneously varying position and torque produced ankle impedance estimates that could not be predicted based on the estimates produced when position and torque varied independently. These results highlight the inherently non-linear behavior of the ankle during movement tasks, and emphasize caution when trying to predict impedance during natural movement tasks.
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08:15-08:30, Paper ThAT11.2 | |
Conceptual Diversity in Leg Mechanics Inspires Biomimetic Prostheses for Walking and Running (I) |
Adamczyk, Peter Gabriel | Univ. of Wisconsin - Madison |
Keywords: Human performance - Gait
Abstract: Biomechanical devices are shaped by the ways they try to mimic the natural body, including geometric, structural, and control properties. Different conceptual models lead to different solutions. We present a new perspective and method to describe ankle control across walking and running, and an adaptive foot-ankle prosthesis that mimics the behavior.
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08:30-08:45, Paper ThAT11.3 | |
Accuracy and Precision of Ankle Joint Stiffness Regulation (I) |
Wind, Alexander | Northwestern Univ |
Rouse, Elliott | Univ. of Michigan |
Keywords: Human performance - Sensory-motor, Neuromuscular systems - Locomotion, Motor neuroprostheses - Robotics
Abstract: Current models of human biomechanics consisting only of joint torques and joint angles are insufficient to completely describe lower-limb gait dynamics. The agonist-antagonist neuromuscular geometry permits regulation of joint impedance, in addition to joint torques and angles. Joint impedance governs the instantaneous response to a perturbation, and is implicated in energy storage, dissipation, and exchange. Despite knowledge of how joint impedance changes throughout the gait cycle, little is known about the role of these properties in neuromotor control. The purpose of this study was to quantify the accuracy and precision of ankle stiffness control, and compare these data to the regulation of ankle torque and position. Our results showed that both the accuracy and precision of matching ankle stiffness to a desired target were not significantly different from analogous torque or position target-matching tasks.
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08:45-09:00, Paper ThAT11.4 | |
A Model of Muscle Excitations Applied to Predictive Robust Control of Wearable Robots (I) |
Pons, Jose Luis | Cajal Inst. Spanish Res. Council |
Keywords: Neuromuscular systems - Locomotion, Neurorehabilitation, Neural signal processing
Abstract: The nervous system simplifies neuromuscular control by using muscle synergies, thus organizing muscle activity into a small number of coordinative modules. In the present study we investigated how muscle modularity is structured across a broad range of walking conditions including different speeds and ground elevations. This descriptive analysis of muscle modularity can then be translated into a predictive model to estimate how motor components modulate across locomotion speeds and ground elevations, which in turn, can inform human to WR interfaces for a robust and natural operation.
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|
09:00-09:15, Paper ThAT11.5 | |
Mimicking Human Control of Stance Leg Improves Prosthesis Control (I) |
Thatte, Nitish | Carnegie Mellon Univ |
Kyung, Timothy | Carnegie Mellon Univ |
Senthilnathan, Chendur | Carnegie Mellon Univ |
Geyer, Hartmut | Carnegie Mellon Univ |
Keywords: Neuromuscular systems - Computational modeling, Neuromuscular systems - Locomotion, Human performance - Gait
Abstract: It is well understood that the whole body mechanics of human locomotion are characterized by compliant leg behavior in stance. While in some animals this behavior is realized by passive leg mechanics, it requires control in humans. In the past, several suggestions have been made about what challenges this control faces and how solutions may be realized by the human nervous system. In current work, we are interested in understanding whether mimicking the proposed human control in powered prostheses can improve the stability and robustness of amputee gait. In initial results, we find that it stabilizes gait after slipping events substantially more often than impedance control.
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09:15-09:30, Paper ThAT11.6 | |
Efference Copy and Its Implications for Robotic Lower Limb Prostheses (I) |
Ferris, Daniel | Univ. of Florida |
Keywords: Neuromuscular systems - Locomotion, Motor neuroprostheses - Prostheses, Neuromuscular systems - Peripheral mechanisms
Abstract: Efference copy is a neural signal mirroring the command from the motor cortex to the periphery that activates the muscles. It provides information necessary for the nervous system to predict expected sensory feedback in the control of movement. Most robotic lower limb prostheses decouple or alter the relationship between efference copy and the predicted sensory feedback. As a result, the use of robotic lower limb prostheses and exoskeletons can be difficult to control and may provide a sensation of perturbation rather than coordinated motion. Control approaches that integrate efferent signals can reduce perturbation perceptions and may generate a more naturalistic movement pattern when merging machines with humans.
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ThAT12 |
Meeting Room 321A |
Invited Session: Multiscale Complexity Analysis of Biomedical Signals:
Methods and Applications (a2nq5) |
Invited Session |
Chair: Faes, Luca | Univ. of Palermo |
Co-Chair: Porta, Alberto | Univ. Degli Studi Di Milano |
Organizer: Faes, Luca | Univ. of Palermo |
Organizer: Porta, Alberto | Univ. Degli Studi Di Milano |
|
08:00-08:15, Paper ThAT12.1 | |
Circadian Rhythm of Multiscale Complexity of Short-Term Cardiac Control (I) |
Porta, Alberto | Univ. Degli Studi Di Milano |
De Maria, Beatrice | IRCCS Fondazione Salvatore Maugeri, Milano |
Cairo, Beatrice | Univ. Degli Studi Di Milano |
Bari, Vlasta | IRCCS Pol. San Donato |
Keywords: Physiological systems modeling - Signal processing in physiological systems, Physiological systems modeling - Signals and systems
Abstract: We applied a recently proposed multiscale complexity (MSC) method to heart period (HP) variability to verify whether complexity of the cardiac control at temporal scales typical of sinus node neural regulation exhibits a circadian rhythm. MSC analysis was performed on 24h Holter HP variability recordings during daytime and nighttime in 12 healthy humans (age: 34-55 yr). We found that HP complexity in the range of frequencies below the respiratory band increased during nighttime. We conclude that the increase of cardiac control complexity during nighttime is mainly due to sympathetic withdrawal more than vagal activation.
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08:15-08:30, Paper ThAT12.2 | |
Performance of Refined Multiscale Entropy in the Nociception Assessment, Implementing a Fuzzy Approach (I) |
Valencia Murillo, Jose Fernando | Univ. San Buenaventura |
Bolaños, José Daniel | Univ. San Buenaventura |
Vallverdu, Montserrat | Univ. Pol. De Catalunya |
Jensen, Erik Weber | Tech. Univ. of Catalonia |
Porta, Alberto | Univ. Degli Studi Di Milano |
Gambus, Pedro L | Hospital CLINIC, Univ. De Barcelona, |
Keywords: Nonlinear dynamic analysis - Biomedical signals
Abstract: Fuzzy entropy (FuzEn), instead of sample entropy (SampEn), was implemented in Refined Multiscale Entropy (RMSE) applied to EEG signals, in order to predict pain responses in patients under sedation-analgesia. EEG segments were classified according to Ramsay sedation score (RSS) values in two groups: with response (2≤RSS≤5) and without response (RSS=6) to noxious stimuli. FuzEn had better nociception prediction in long scales than SampEn.
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08:30-08:45, Paper ThAT12.3 | |
Multiscale Entropy As a Tool for Complexity Analysis and Nonlinearity Detection in Cardiovascular Oscillations (I) |
Silva, Luiz Eduardo Virgilio | School of Medicine of Ribeirão Preto |
Rodrigues, Fernanda L. | School of Medicine of Ribeirão Preto |
Bari, Vlasta | IRCCS Pol. San Donato |
Oliveira, Mauro | School of Medicine of Ribeirão Preto |
Fazan Jr, Rubens | School of Medicine of Ribeirão Preto |
Porta, Alberto | Univ. Degli Studi Di Milano |
Keywords: Nonlinear dynamic analysis - Biomedical signals
Abstract: Multiscale entropy (MSE) has long been recognized as a complexity measurement. Recently, MSE was also applied as a discriminant statistic for a nonlinearity test of heart rate variability series. Here, we applied MSE and refined MSE as both complexity and nonlinearity measurements of arterial pressure (AP) oscillations in a mice model of baroreflex denervation. Results showed that AP contains reasonable levels of nonlinearity, but they are independent of the baroreflex. Moreover, complexity decreased when the baroreflex was removed, pointing that the two concepts might bring complementary information.
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08:45-09:00, Paper ThAT12.4 | |
Multiscale Entropy Analysis of Short Cardiovascular Variability Series During Orthostatic and Mental Stress (I) |
Javorka, Michal | Comenius Univ. Jessenius Faculty of Medicine |
Porta, Alberto | Univ. Degli Studi Di Milano |
Nollo, Giandomenico | Univ. of Trento |
Faes, Luca | Univ. of Palermo |
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|
09:00-09:15, Paper ThAT12.5 | |
Multiscale Partial Information Decomposition of Neural and Cardiovascular Signals (I) |
Faes, Luca | Univ. of Palermo |
Bari, Vlasta | IRCCS Pol. San Donato |
Ranucci, Marco | Department of Cardiothoracic, Vascular Anesthesia and Intensive |
Marinazzo, Daniele | Faculty of Psychology and Educational Sciences, Department of Da |
Stramaglia, Sebastiano | Univ. of Bari, Italy, and INFN Sezione Di Bari, Italy |
Porta, Alberto | Univ. Degli Studi Di Milano |
Keywords: Physiological systems modeling - Multivariate signal processing, Directionality, Physiological systems modeling - Signal processing in physiological systems
Abstract: We present the extension to multiscale analysis of Partial Information Decomposition, a recently proposed information-theoretic framework to dissect the information transferred within a network of interacting signals. The extension is based on the theory of state-space models, and leads to assess unique, redundant and synergistic information transfer as a function of the temporal scale at which the signals are observed. The usefulness of this new framework for the clinical study of physiological networks is demonstrated in the analysis of brain dynamics and cardiovascular control.
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09:15-09:30, Paper ThAT12.6 | |
Multiscale Granger Causality of RR and QT Interval Variability (I) |
Baumert, Mathias | The Univ. of Adelaide |
Faes, Luca | Univ. of Palermo |
Porta, Alberto | Univ. Degli Studi Di Milano |
Keywords: Causality, Physiological systems modeling - Multivariate signal processing
Abstract: Beat-to-beat variability of the QT interval in ECG is closely linked to heart rate variability. Here, we explore this relationship on multiple time scales, and the effect of ageing by estimating Granger causality. We observe a bidirectional coupling, predominately from heart rate to QT variability that is strongest on the original time scale and weakens with age.
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ThAT13 |
Meeting Room 321B |
Invited Session: Time-Series Modelling of Physiology: Inference,
Implementation, and Interpretability (j63dh) |
Invited Session |
Chair: Colopy, Glen Wright | Univ. of Oxford |
Co-Chair: Bergmann, Jeroen | Univ. of Oxford |
Organizer: Casson, Alexander James | The Univ. of Manchester |
Organizer: Clifton, David | Univ. of Oxford |
Organizer: Colopy, Glen Wright | Univ. of Oxford |
|
08:00-08:15, Paper ThAT13.1 | |
Machine Learning for Time-Series Inference When Identifying the Deteriorating Patient (I) |
Clifton, David | Univ. of Oxford |
Colopy, Glen Wright | Univ. of Oxford |
Shamout, Farah | Univ. of Oxford |
Clifton, Lei | Univ. of Oxford |
Zhu, Tingting | Univ. of Oxford |
Keywords: General and theoretical informatics - Big data analytics, Health Informatics - Clinical information systems, Health Informatics - Electronic health records
Abstract: The identification of patient deterioration is a critical factor in providing timely and effective medical care; major physiological events are typically preceded by derangement of those physiological data that are now routinely collected in many hospitals. However, the parsing of continuous multivariate time-series data acquired minute-by-minute for very large cohorts of hospital patients is not a task that is well-suited for humans. We outline advances in the field of machine learning for modelling time-series physiological data acquired from hospital patients, and describe how such a system can provide a continuous screening facility that enables human expertise to be brought to the bedside in a timely manner, for those patients most at risk of imminent physiological deterioration.
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08:15-08:30, Paper ThAT13.2 | |
Time-Series versus IID Features in Machine Learning for Vital-Sign Monitoring (I) |
Colopy, Glen Wright | Univ. of Oxford |
Roberts, Stephen | Univ. of Oxford |
Clifton, David | Univ. of Oxford |
Keywords: General and theoretical informatics - Algorithms, General and theoretical informatics - Artificial Intelligence, General and theoretical informatics - Big data analytics
Abstract: The probabilistic modelling of vital-signs is a key tool to understand the variability in both patient physiology and the measurement of that physiology. Vari- ability in vital-sign measurements may correlate across time and across other vital signs, or may result from measurement noise. Current clinical practice in patient monitoring (e.g., the Nation Early Warning Score) ignore the noise, time-dependence, and inter-vital-sign covariance. Modelling methods of time-series tend to either (i) model time-dependent correlation directly, or (ii) derive a set of descriptive IID features from the time-series. Popular meth- ods to model multiple vital-sign time-series (e.g. Kalman filtering, vector auto-regression, or Gaussian processes) model both time and inter-vital-sign correlation, but do so by making unreasonable assumptions about the marginal distributions of the individual vital signs (e.g. Gaussian noise or log-Gaussian noise, after a data transformation). This paper describes how copulas may serve as a simple modelling tool to create principled estimates of the joint density between vital signs. Using heart rate, respiratory rate, and SpO2 as exemplars, we begin by learning an optimal marginal distribution family to describe IID noise for each vital sign. Time-series properties of IID correlation is then examined.
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08:30-08:45, Paper ThAT13.3 | |
A Multitasking Paradigm to Establish Patient Specific Changes During Everyday Activities in Parkinson’s Disease (I) |
Bergmann, Jeroen | Univ. of Oxford |
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|
ThAT14 |
Meeting Room 322AB |
Minisymposia: Cuffless Unobtrusive Blood Pressure Measurement: From
Sensing, Mechanism, Algorithm to Standardization (99i3h) |
Minisymposium |
Chair: Tamura, Toshiyo | Waseda Univ |
Co-Chair: Carey, Carole C. | Former U.S. Food and Drug Administration |
Organizer: Ding, Xiao-Rong | Univ. of Oxford |
Organizer: Carey, Carole C. | Former U.S. Food and Drug Administration |
|
08:00-08:15, Paper ThAT14.1 | |
Developing Cuffless Blood Pressure Monitoring Devices in Japanese Industries (I) |
Tamura, Toshiyo | Waseda Univ |
|
|
08:15-08:30, Paper ThAT14.2 | |
The Effect of Measurement Condition on Cuffless and Continuous Monitoring of Blood Pressure in Daily Life (I) |
Maeda, Yuka | Univ. of Tsukuba |
Sekine, Masaki | Osaka Electro-Communication Univ |
Tamura, Toshiyo | Waseda Univ |
Mizutani, Koichi | Univ. of Tsukuba |
Keywords: Optical and photonic sensors and systems, Sensor systems and Instrumentation, Wearable body sensor networks and telemetric systems
Abstract: Pulse wave velocity (PWV) has a correlation with blood pressure (BP) and has been reported to be suitable for cuffless and continuous BP monitoring. On the other hand, BP monitors are extremely sensitive to measurement site position. For this reason, PWV may also be affected by the arm-position change. The aim of this study was to verify the effect of the arm-position in BP estimation by using PWV. The results showed that the movement of the elbow joint had a little effect on PAT and PTT measurements.
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08:30-08:45, Paper ThAT14.3 | |
Effect of Variation of Pressure Dependency of Arterial Stiffness on Estimation of Blood Pressure from Pulse Transit Time: Implications for Cuffless Measurement of Blood Pressure (I) |
Avolio, Alberto P | Macquarie Univ |
Shirbani, Fatemeh | Macquarie Univ. Faculty of Medicine and Health Sciences |
Tan, Isabella | Macquarie Univ |
Butlin, Mark | Macquarie Univ |
Keywords: Physiological monitoring - Modeling and analysis
Abstract: Pulse transit tine (PTT) is the surrogate parameter for cuffless measurement of arterial blood pressure (BP). The association between BP and PTT is determined by the pressure dependency of arterial stiffness measured as pulse wave velocity (PWV = distance/PTT). The sensitivity of PWV to BP is not uniform and varies with BP. Due to this characteristic, similar changes in PTT will result in different errors in BP estimation depending on the level of BP. This may have implication for accuracy of cuffless BP measurement when PTT is measured by skin surface sensors.
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|
ThAT15 |
Meeting Room 323A |
Invited Session: Analysis of Cardiac Vibrations: Methodology and
Applications (718fu) |
Invited Session |
Chair: Di Rienzo, Marco | Fondazione Don Carlo Gnocchi |
Co-Chair: Inan, Omer | Georgia Inst. of Tech |
Organizer: Di Rienzo, Marco | Fondazione Don Carlo Gnocchi |
Organizer: Inan, Omer | Georgia Inst. of Tech |
|
08:00-08:15, Paper ThAT15.1 | |
Applications of Multidimensional Motion Sensors in Cardiovascular Monitoring and Medical Imaging (I) |
Jafari Tadi, Mojtaba | Univ. of Turku |
Lahdenoja, Olli | Tech. Res. Center, Univ. of Turku |
Lehtonen, Eero Lennart | Univ. of Turku |
Hurnanen, Tero | Tech. Res. Center, Univ. of Turku |
Mehrang, Saeed | Tampere Univ. of Tech |
Pänkäälä, Mikko | Univ. of Turku |
Koivisto, Tero | Univ. of Turku |
|
|
08:15-08:30, Paper ThAT15.2 | |
Evaluation of Relative Goodness of Seismocardiography (SCG) to ECG for Multimodal Cardiac Quiescence Prediction (I) |
Yao, Jingting | Georgia Inst. of Tech |
Tridandapani, Srini | Emory Univ |
Auffermann, William | Univ. of Utah |
Wick, Carson A | Emory Univ |
Bhatti, Pamela | Georgia Inst. of Tech |
Keywords: Cardiovascular and respiratory signal processing - Cardiovascular signal processing, Coronary artery disease
Abstract: This work investigates the relative goodness of seismocardiography (SCG) to ECG in predicting cardiac quiescence. As a baseline, quiescence derived from patient-specific echocardiography is used for comparing quiescence derived from ECG- and combined ECG-SCG-based methods. Numerically derived as an SCG index and validated by the baseline echocardiography, our results indicate that the SCG index is an effective measure in distinguishing subjects who would benefit from a multimodal (ECG and SCG) quiescence prediction, compared with an ECG-only-based prediction. The development of SCG index enables a more comprehensive multimodal framework for cardiac gating of imaging modalities such as computed tomography (CT) and magnetic resonance imaging.
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|
08:30-08:45, Paper ThAT15.3 | |
Caveats in the Analysis of Prolonged Seismocardiogram Recordings (I) |
Di Rienzo, Marco | Fondazione Don Carlo Gnocchi |
Vaini, Emanuele | IRCCS Pol. San Donato |
Lombardi, Prospero | Fondazione Don Carlo Gnocchi ONLUS |
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|
08:45-09:00, Paper ThAT15.4 | |
Gyrocardiography: A Preliminary Investigation of Cardiac Timings (I) |
Kheirkhah Dehkordi, Parastoo | Univ. of British Columbia |
Tavakolian, Kouhyar | Assistant Professor |
Khosrow-khavar, Farzad | Simon Fraser Univ |
Keywords: Cardiovascular and respiratory signal processing - Cardiovascular signal processing
Abstract: Gyrocardiography (GCG) is a non-invasive method for measuring the angular velocity of the chest caused by heart motion. In this study, we assessed the reliability and accuracy of GCG as a promising technology for measuring the cardiac timing intervals. We recorded the 3-axial GCG signals from 50 healthy volunteers. In addition, the electrocardiogram (ECG) and the tissue Doppler Imaging (TDI) were recorded, simultaneously. We identified several cardiac fiducial points on the GCG x- and y-axis signals and estimated the cardiac time intervals from ECG Q to the delineated points. We labelled mitral and aortic valve opening and closure on TDI images and measured the time intervals from ECG Q to the TDI points as the gold reference. We assessed the agreement between the estimated and reference time intervals using the Bland-Altman technique. The analysis of results showed that delineation of the fiducial points on the GCG x- and y-axis was not available for 30% and 20% of cycles, respectively. In comparison to GCG x-axis, the GCG y-axis time intervals had smaller bias and variability with reference to the TDI measurements, which shows that the GCG y-axis estimates provide better approximations for cardiac intervals. However, the finding of this study does not confirm that CGC is an accurate tool for measuring the cardiac timing intervals.
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|
09:00-09:15, Paper ThAT15.5 | |
Longitudinal Ballistocardiogram and Electrocardiogram Measurements from Patients with Heart Failure at Home: Results from the Ongoing Studies and Lessons Learned (I) |
Shandhi, Md. Mobashir Hasan | Georgia Inst. of Tech |
Klein, Liviu | Univ. of California, San Francisco |
Fan, Joanna | Univ. of California, San Francisco |
Etemadi, Mozziyar | Northwestern Univ |
Inan, Omer | Georgia Inst. of Tech |
Keywords: Cardiovascular, respiratory, and sleep devices - Sensors
Abstract: This minisymposium contribution focuses on the ongoing studies where we have provided ballistocardiogram (BCG) and electrocardiogram (ECG) sensing weighing scales to patients with heart failure (HF) for serial measurements at home. The BCG is a measurement of the mechanical aspects of cardiovascular function. The ultimate goal of the study is to assess whether BCG and ECG signals can provide value in predicting exacerbations for patients with HF at home, and thus be used to titrate care remotely. Thus far, we have recruited a total of 16 patients with HF for a total of 425 patient-days of recordings. Of these recordings, 365 were found to be usable based on signal quality indices (i.e., signal-to-noise ratio). Moreover, in one subject, the variability of BCG signal parameters over time was high at the beginning of the 30-day recording period, then stabilized at the end – this subject had inadvertently placed himself on a beta-blocker for the period of variability. We will present the findings thus far from our study, and discuss key lessons we have learned.
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ThAT16 |
Meeting Room 323B |
Invited Session: Next Steps in Real-Life Brain Monitoring: Technologies for
Wearable EEG (9xrw2) |
Invited Session |
Chair: Casson, Alexander James | The Univ. of Manchester |
Co-Chair: Hairston, W. David | Us Army Res. Lab |
Organizer: Casson, Alexander James | The Univ. of Manchester |
Organizer: Hairston, W. David | Us Army Res. Lab |
Organizer: De Vos, Maarten | Univ. of Oxford |
Organizer: Kidmose, Preben | Aarhus Univ. Denmark |
|
08:00-08:15, Paper ThAT16.1 | |
Dry-Contact Electrode Ear-EEG (I) |
Kappel, Simon Lind | Aarhus Univ. Denmark |
Kidmose, Preben | Aarhus Univ. Denmark |
Keywords: Neural interfaces - Bioelectric sensors, Neural interfaces - Tissue-electrode interface, Neural interfaces - Body interfaces
Abstract: Ear-EEG is a recording method where EEG signals are acquired from electrodes placed on an earpiece inserted into the ear. Previously reported ear-EEG recordings have been performed with wet electrodes, and the objective of this study was to develop and evaluate dry-contact electrode ear-EEG. A novel dry-contact ear-EEG platform, comprising electrodes embedded in a soft-earpiece, was developed. The platform was evaluated in a study of four EEG paradigms: auditory steady-state response, steady-state visual evoked potential, mismatch negativity, and alpha band modulation. With both the measuring electrode and the reference electrode located within the ear, statistically significant (p<0.05) responses were measured for all paradigms, although for mismatch negativity it was necessary to use a reference located in the opposite ear, to obtain a statistically significant response. The prototyped dry-contact ear-EEG platform represents an important technological advancement of the method in terms of user-friendliness and suitability for long-term use.
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08:15-08:30, Paper ThAT16.2 | |
Overcoming Obstacles in Mobile EEG (I) |
Nordin, Andrew D. | Univ. of Florida |
Hairston, W. David | Us Army Res. Lab |
Ferris, Daniel | Univ. of Florida |
Keywords: Neuromuscular systems - Locomotion, Neural interfaces - Bioelectric sensors, Neural signal processing
Abstract: We used high-density electroencephalography (EEG) to evaluate electrocortical dynamics during obstacle navigation using a novel dual-layer electrode approach for noise cancellation. After validating the technique on a phantom head, we collected data from subjects walking and running on a treadmill as they stepped over obstacles. Data revealed event related synchronizations in premotor, primary motor, and posterior parietal cortices tied to obstacles appearing on the treadmill. The results show it is possible to document the timing of brain network activity synchronized to reactive adjustments in human locomotion using mobile EEG.
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08:30-08:45, Paper ThAT16.3 | |
Future Challenges in Sleep Monitoring with Wearable EEG (I) |
Imtiaz, Syed Anas | Imperial Coll. London |
Garcia Lopez, Irene | Imperial Coll. of London |
Rodriguez-Villegas, Esther | Imperial Coll. London |
Keywords: Neural signal processing
Abstract: This paper looks at the existing state-of-the-art use of wearable EEG in the area of sleep monitoring and the future challenges for the development of EEG-based wearable systems for the diagnosis of neurological sleep disorders.
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|
08:45-09:00, Paper ThAT16.4 | |
Real-Time Closed Loop EEG Systems with Electrical, Auditory, and App Based Visual Feedback (I) |
Casson, Alexander James | The Univ. of Manchester |
Jacob, Nikhil Kurian | Univ. of Manchester |
Kohli, Siddharth | The Univ. of Manchester |
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|
09:00-09:15, Paper ThAT16.5 | |
Comfortable and Safe Dry EEG Electrodes for Real-World Neuroimaging (I) |
Bradford, J. Cortney | U. S. Army Res. Lab |
Bottomley, Summer | U.S. Army Res. Lab |
Slipher, Geoffrey A. | U.S. Army Res. Lab |
Hairston, W. David | Us Army Res. Lab |
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|
09:15-09:30, Paper ThAT16.6 | |
New Approaches in Validating EEG System and Electrode Performance (I) |
Hairston, W. David | Us Army Res. Lab |
Yu, Alfred | US Army Res. Lab |
Slipher, Geoffrey A. | U.S. Army Res. Lab |
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|
ThAT17 |
Meeting Room 323C |
Invited Session: MULTI-TECHNOLOGIES-PLATFORMS: ADVANCED SENSORS AND
ACTUATORS FOR LIFE SCIENCE APPLICATIONS (7p8b4) |
Invited Session |
Chair: Miled, Amine | Laval Univ |
Co-Chair: Ghafar-Zadeh, Ebrahim | York Univ |
Organizer: Miled, Amine | Laval Univ |
Organizer: Ghafar-Zadeh, Ebrahim | York Univ |
Organizer: Boukadoum, Mounir | Univ. of Quebec at Montréal |
Organizer: Izquierdo, Ricardo | École De Tech. Supérieure |
Organizer: Chen, JIe | Univ. of Alberta |
Organizer: Magierowski, Sebastian | York Univ |
|
08:00-08:15, Paper ThAT17.1 | |
Low-Power, Miniature Wireless Sensor Design for Biomedical Applications: Oximeter and Heart Rate Monitor Example (I) |
Boukadoum, Mounir | Univ. of Quebec at Montréal |
|
|
08:15-08:30, Paper ThAT17.2 | |
Detecting Gold Nanoparticles Covalently Bound to Interdigitated Gold Electrode Substrates for Applications in Biosensing (I) |
MacKay, Scott | Univ. of Alberta |
Abdelrasoul Mohamed, Gaser Nagah | Univ. of Alberta |
Tamura, Marcus | Univ. of Alberta |
Lin, Donghai | Univ. of Alberta |
Chen, JIe | Univ. of Alberta |
Keywords: Clinical laboratory, assay and pathology technologies, Diagnostic devices - Physiological monitoring
Abstract: A biosensor system has been developed and tested which uses microfabricated gold electrodes which are chemically modified. Gold nanoparticles were chemically bound to the electrodes and a resulting electrical impedance change was measured. This type of test can be modified with biological components to create a versatile biosensor system for medical diagnostics, environmental monitoring, and research applications.
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|
08:30-08:45, Paper ThAT17.3 | |
3rd Generation DNA Sequencing with Embedded Neural Networks (I) |
Zhong, Xiaoyong | York Univ |
Wu, Zhongpan | York Univ |
Ghafar-Zadeh, Ebrahim | York Univ |
Magierowski, Sebastian | York Univ |
Keywords: Clinical laboratory, assay and pathology technologies, Diagnostic devices - Physiological monitoring
Abstract: 3rd generation nucleic acid sensors allow raw DNA/RNA measurements to be gathered at high rates in small, mobile platforms. However the computing resources needed to accurately predict nucleotide sequences from the raw measurements "at speed" are substantial and preclude portability. As a step towards addressing this issue, we present a recurrent neural network hardware design intended for embedded nucleic acid basecalling within the sequencing pipeline.
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|
08:45-09:00, Paper ThAT17.4 | |
Printed Sensors on Flexible Substrates for Biomedical Applications (I) |
Descent, Philippe | École De Tech. Supérieure |
Izquierdo, Ricardo | École De Tech. Supérieure |
Keywords: Diagnostic devices - Physiological monitoring, Wearable or portable devices for vital signal monitoring
Abstract: Printed electronics has become of great interest over the last few years due to its advantages of a reduction of fabrication cost and the possibility to print on flexible substrates. Here we present the fabrication of temperature and humidity sensors by using thermal transfer printed interdigitated electrodes covered by graphene oxide. Graphene oxide acts as the temperature and humidity sensing material by changing its electrical properties as a function of the ambient conditions. These type of printed sensors could easily be integrated into biomedical applications such as smart bandages.
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|
09:00-09:15, Paper ThAT17.5 | |
Towards an Optofluidic System for Neurotransmitter Detection (I) |
Niyonambaza, Shimwe Dominique | Univ. Laval |
Boisselier, Elodie | Univ. Laval |
Boukadoum, Mounir | Univ. of Quebec at Montréal |
Miled, Amine | Laval Univ |
Keywords: Diagnostic devices - Physiological monitoring, Clinical laboratory, assay and pathology technologies, Neuromodulation devices
Abstract: We present preliminary work on the detection of neurotransmitters (NTs) in a microfluidic channel by visible light spectroscopic means. NTs are not active in the visible spectrum in general, and that complicates their detection by direct spectroscopic methods. Nevertheless, some NTs interfere with the absorption spectrum of gold nanoparticles (AuNPs) by shifting their 524 nm maximum absorbance wavelength. This opens the door to NT detection with visible light optical means, in addition to the possibility to integrate the whole system on a single chip for continuous measurement in real time.
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|
09:15-09:30, Paper ThAT17.6 | |
Core-CBCM CMOS Capacitive Sensors for Life Science Applications: Recent Progresses and Future Prospects (I) |
Ghafar-Zadeh, Ebrahim | York Univ |
|
|
ThAT18 |
Meeting Room 324 |
Minisymposia: TOWARDS P4 MEDICINE IN SLEEP THERANOSTICS III (1i8t5) |
Minisymposium |
Chair: Khoo, Michael | Univ. of Southern California |
Co-Chair: Penzel, Thomas | Charite Univ. Berlin |
Organizer: Khoo, Michael | Univ. of Southern California |
Organizer: Penzel, Thomas | Charite Univ. Berlin |
|
08:00-08:15, Paper ThAT18.1 | |
Continued Evolution of Telemedicine & Personalised Care in Sleep and Respiratory Medicine (I) |
Armitstead, Jeffrey Peter | Res. Ltd., Univ. of Sydney |
Javed, Faizan | Univ. of New South Wales |
Schindhelm, Klaus | Univ. of New South Wales |
Keywords: Sleep - Sleep apnea therapy, Sleep - Obstructive sleep apnea, Sleep - Periodic breathing & central apnea
Abstract: Connected devices for the treatment of sleep and respiratory disorders continue to evolve and enable telemonitoring, remote personalization and enriched patient engagement; elements of the P4 medicine paradigm. Recent database analyses and efforts in patient phenotyping have shown that personalized treatment is possible with the potential for improved compliance to chronic therapy.
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08:15-08:30, Paper ThAT18.2 | |
Loop Gain As a Biomarker of Ventilatory Instability and Its Utility in Predicting the Response to Therapies for Sleep-Disordered Breathing (I) |
Edwards, Bradley Allan | Monash Univ |
Terrill, Philip Ian | Univ. of Queensland |
Landry, Shane | Monash Univ |
Joosten, Simon | Monash Health and Monash Univ |
Owens, Robert | Harvard Medical School |
Malhotra, Atul | Brigham and Women's Hospital and Harvard Medical School |
White, David P | Brigham and Women's Hospital and Harvard Medical School |
Wellman, David Andrew | Harvard Medical School |
Hamilton, Garun | Department of Res. and Sleep Medicine, Monash Medical Cen |
Sands, Scott Aaron | Brigham and Women's Hospital and Harvard Medical School |
Keywords: Sleep - Obstructive sleep apnea, Sleep - Sleep apnea therapy
Abstract: The sensitivity/stability of the ventilatory control system (often described by loop gain) is important in the pathophysiology of both central sleep apnea (CSA) and obstructive sleep apnea (OSA). In this presentation, we will review: (1) the current methods available to assess an individual’s loop gain; (2) interventions that can employed to manipulate it; and (3), whether knowledge of an individual’s underlying ventilatory sensitivity can help predict responses to commonly recommended treatments for these sleep-related breathing disorders.
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08:30-08:45, Paper ThAT18.3 | |
Revisiting Plant Gain: New Observations and Extended Models (I) |
Khoo, Michael | Univ. of Southern California |
Nava-Guerra, Leonardo | Univ. of Southern California |
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08:45-09:00, Paper ThAT18.4 | |
Advances in Sleep Theranostics – What’s Next? (I) |
Khoo, Michael | Univ. of Southern California |
Penzel, Thomas | Charite Univ. Berlin |
Keywords: Sleep - Obstructive sleep apnea, Sleep - Sleep apnea therapy, Sleep - Snoring
Abstract: This last time-slot for the series of 3 back-to-back minisymposia covering the theme covering the theme: TOWARDS “P4 MEDICINE” IN SLEEP THERANOSTICS is dedicated to a general discussion of highlights from the presentations made by the minisymposia speakers, as well as the most recent advances in the field not covered in the previous papers.
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ThAT19 |
Meeting Room 325A |
Minisymposia: Emerging Methods in Medical Image Analysis I (1agah) |
Minisymposium |
Chair: Fujita, Hiroshi | Gifu Univ |
Co-Chair: Lee, Gobert | Flinders Univ |
Organizer: Fujita, Hiroshi | Gifu Univ |
Organizer: Lee, Gobert | Flinders Univ |
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08:00-08:15, Paper ThAT19.1 | |
Future Directions for Biomedical Image Analysis in the Broader Health Data Context (I) |
maeder, anthony john | Flinders Univ. School of Nursing & Health Sciences |
Keywords: Image analysis and classification - Machine learning / Deep learning approaches
Abstract: This paper presents a case for inclusion of non-image data to extend the effectiveness of biomedical image analysis algorithms, and conversely the inclusion of elements of information derived from image data to improve “big data” approaches to the personalization of health care. It has been argued that this expansion of current practice could yield performance improvements as well as allowing differentiation of patient cohorts on a more systematic basis.
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08:15-08:30, Paper ThAT19.2 | |
Automated Intelligent Systems for the Analysis of Optical Coherence Tomography Images in Eye and Skin Applications (I) |
Wong, Damon | Inst. for Infocomm Res |
Yow, Ai Ping | Inst. for Infocomm Res |
Cheng, Jun | Inst. of Biomedical Engineering, Chinese Acad. of Sciences |
Fu, Huazhu | Inst. for Infocomm Res. A*STAR |
Srivastava, Ruchir | Inst. for Infocomm Res |
Lee, Beng Hai | Inst. for Infocomm Res |
Ong, Ee Ping | Inst. for Infocomm Res |
Liu, jiang | Ningbo Inst. of Materials Tech. and Engineering, CAS |
Keywords: Optical imaging - Coherence tomography, Ophthalmic imaging and analysis
Abstract: Optical coherence tomography allows in vivo, non-invasive imaging of tissue. We present two systems developed for the analysis of OCT images. AGARPLUS is developed for anterior segment ophthalmic imaging to automatically segment, measure and differentiate glaucoma subtypes. ASHIMA is developed for dermatological imaging to identify and separate the components of a skin OCT image for enhanced visualization and assessment of skin layers. Such systems could assist clinicians in the analysis of OCT images, with potential applications in screening and workflow improvement.
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08:30-08:45, Paper ThAT19.3 | |
Retinal Image Analysis Using Convolutional Neural Network (I) |
Hatanaka, Yuji | Univ. of Shiga Prefecture |
Ikawa, Hibiki | Univ. of Shiga Prefecture |
Miyashita, Mitsuhiro | The Univ. of Shiga Prefecture |
Sunayama, Wataru | The Univ. of Shiga Prefecture |
Ogohara, Kazunori | Univ. of Shiga Prefecture |
Muramatsu, Chisako | Gifu Univ |
Fujita, Hiroshi | Gifu Univ |
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08:45-09:00, Paper ThAT19.4 | |
Detection of Nerve Fiber Layer Defect on Retinal Fundus Images for Early Diagnosis of Glaucoma (I) |
Muramatsu, Chisako | Gifu Univ |
Watanabe, Ryusuke | Gifu Univ |
Ishida, Kyoko | Toho Univ. Ohashi Medical Center |
Sawada, Akira | Gifu Univ |
Hatanaka, Yuji | Univ. of Shiga Prefecture |
Yamamoto, Tetsuya | Gifu Univ |
Fujita, Hiroshi | Gifu Univ |
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09:00-09:15, Paper ThAT19.5 | |
Identification of Prognostic Imaging Biomarkers for Hepatocellular Carcinoma Based on Radiogenomics and Multiregion Analysis (I) |
Xia, Wei | Suzhou Inst. of Biomedical Engineering and Tech. Chine |
Chen, Ying | Suzhou Inst. of Biomedical Engineering and Tech. Chine |
Zhang, Bo | Second Affiliated Hospital of Soochow Univ |
Gao, Xin | Suzhou Inst. of Biomedical Engineering and Tech. Chine |
Keywords: Image feature extraction, CT imaging applications
Abstract: To identify prognostic imaging biomarkers in hepatocellular carcinoma (HCC) with biological interpretations by associating imaging features and gene modules. For the patients with CECT imaging data and gene expression profiles, intra-tumor partition was performed resulting in three spatially distinct subregions. Quantitative imaging features were extracted from each subregion. Prognostic gene modules were obtained, and their biological functions were annotated. The imaging features that significantly correlated with prognostic gene modules were selected, and their prognostic capabilities for overall survival (OS) were evaluated. The volume fraction of subregion, which was significantly correlated with all prognostic gene modules representing cancer-related interpretation, was predictive of OS. The texture feature cluster prominence in subregion, which was correlated with the prognostic gene module representing lipid metabolism and complement activation, also had the ability to predict OS. Imaging features of subregions have potentials to be predictors of OS with interpretable biological meaning.
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09:15-09:30, Paper ThAT19.6 | |
Application of Deep Learning in Low Dose CT Image Analysis (I) |
Jiang, Huiqin | School of Information Engineering, Zhengzhou Univ |
Gao, Jianbo | The First Affiliated Hospital of Zhengzhou Univ |
Ma, Ling | Information Engineering Inst. of Zhengzhou Univ |
Yang, Haojin | Hasso Plattner Inst. for Digital Engineering Ggmbh |
Keywords: CT imaging, CT imaging applications, Image analysis and classification - Machine learning / Deep learning approaches
Abstract: Deep Learning is particularly suitable for medical imaging analysis. We aim at the characteristics of 3D low dose CT image volume data, and design an automatic segmentation algorithm for three-dimensional lung parenchyma to determine the range of lung cancer screening at high speed. We investigate the traditional solution for CT scan analysis, by which we apply 2D CT slice images and the state-of-the-art deep neural network architecture “Faster RCNN” for lung nodule detection. Moreover, on the basis of the multi task deep neural network architecture, the effective three-dimensional convolution operator is designed and the 3D deep neural network of multi task learning is constructed for this task.
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ThAT20 |
Meeting Room 325B |
Invited Session: Computational Human Models III. High-Frequency Simulations
and Measurements (q6644) |
Invited Session |
Chair: Sayrafian, Kamran | NIST |
Co-Chair: Prakash, Punit | Kansas State Univ |
Organizer: Makarov, Sergey | Electrical and Computer Engineering, Worcester Pol |
Organizer: Horner, Marc | ANSYS, Inc |
Organizer: Noetscher, Gregory | Worcester Pol. Inst |
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08:00-08:15, Paper ThAT20.1 | |
Electric-Field Probe for Field Measurements up to 300 Khz (I) |
Zolj, Adnan | Worcester Pol. Inst |
Makarov, Sergey | Electrical and Computer Engineering, Worcester Pol |
Navarro de Lara, Lucia Isabel | Martinos Center - MGH |
Nummenmaa, Aapo | Massachussetts General Hospital |
Keywords: Health technology - Verification and validation, Clinical engineering, Neuromodulation devices
Abstract: This paper describes an electric field probe that could be used both in air and in a tissue to measure quasi-static electric fields of biomedical instruments from 100Hz to 300kHz. The probe uses a small dipole antenna connected via a long shaft with a simplified Dyson balun to an optical isolation amplifier with low common-mode gain. Induced electric field measured in air are presented for a quasi-static solenoidal field.
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08:15-08:30, Paper ThAT20.2 | |
Simulations of Electric-Field Strength in Different Tissues for a Full-Body Birdcage Resonator Operating at 100-200 Khz (I) |
Bogdanov, Gene | Worcester Pol. Inst |
Appleyard, William | Worcester Pol. Inst |
Noetscher, Gregory | Worcester Pol. Inst |
Deng, Zhi-De | National Inst. of Mental Health |
Nummenmaa, Aapo | Massachussetts General Hospital |
Makarov, Sergey | Electrical and Computer Engineering, Worcester Pol |
Keywords: Muscle stimulation, Neural stimulation (including deep brain stimulation), Computer modeling for treatment planning
Abstract: One major contributor to the degradation of quality of life for a significant portion of the adult population is chronic pain. In many cases, pharmacological solutions are limited in efficacy and alternative treatments, such as Transcutaneous Electrical Nerve Stimulation (TENS), are pursued. This paper describes simulation results that estimate the electric fields generated within an accurate computational human phantom placed within a full-body birdcage resonator operating at 100-200 kHz. The device may operate as a novel and effective TENS device, capable of deep stimulation over large body areas.
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08:30-08:45, Paper ThAT20.3 | |
Radiofrequency Propagation Close to the Human Ear and Accurate Ear Canal Models (I) |
Chen, Louis | Bose Corp |
Eaton, Gerry | Bose Corp |
Noetscher, Gregory | Worcester Pol. Inst |
Makarov, Sergey | Electrical and Computer Engineering, Worcester Pol |
Keywords: Computer model-based assessments for regulatory submissions, Wearable or portable devices for vital signal monitoring
Abstract: Radio frequency wave propagation near the surface of a human body is highly sensitive to a number of items, including skin geometry, material composition and proximity to internal air-filled cavities. This study develops an anatomically realistic model of a human ear canal integrated into a full body computational phantom to address this final factor and examines, through numerical simulation, the impact of this level of detail on the power transmission of two-port and larger networks operating near or on the human body in the UHF band.
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08:45-09:00, Paper ThAT20.4 | |
RF Channel Modeling in Body Area Networks (I) |
Krhac, Katjana | Univ. of Zagreb, Faculty of Electrical Engineering and Comp |
Griffin, Wesley | National Inst. of Standards and Tech |
Sayrafian, Kamran | NIST |
Simunic, Dina | Univ. of Zagreb |
Keywords: Wireless technologies for interrogation of implantable therapeutic devices
Abstract: Comprehensive study of radio waves propagation for ingestible electronics is a very challenging task. Obtaining physical measurements is nearly impossible. And, although limited experimentation on animals or liquid phantom measurements are possible; the results are not quite reflective of the complex and inhomogeneous human body environment. Computational phantoms is another alternative; however, it requires sophisticated human body models along with appropriate transmitter & receiver antenna models. To initiate the study on UWB propagation from a wireless capsule endoscopy, a flexible and interactive immersive platform containing and an enhanced 3D body model has been developed. This platform enables researchers to conduct a comprehensive study of the UWB propagation channel for WCE applications.
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09:00-09:15, Paper ThAT20.5 | |
Efficient Computational Investigation of Implant RF Safety with Anatomical Human Models in MRI Systems (I) |
Prokop, Alexander | CST - a Dassault Systèmes Company |
Wittig, Tilmann | CST - a Dassault Systèmes Company |
Levine, Steven | Dassault Systèmes Simulia |
Keywords: Computer model-based assessments for regulatory submissions, Image-guided devices - MRI-compatible instrumentation and device management, Cochlear implant
Abstract: Implant safety studies typically require a large number of simulations to test the compliance in various positions of the human body model (HBM). Applying the Huygens Box concept allows a significant speed-up of the process. An equivalent field source (EFS) approach is used to efficiently investigate RF safety of various implants in an MRI system. The approach allows to first design the MRI system based on the full simulation domain and then replacing the MRI coil with the equivalent fields on a surface enclosing the patient for following calculations with variations in terms of implant type and location or uncertain tissue properties. SAR distribution shows a good agreement between EFS and full run. A speed-up of a factor of 10 and more depending on the complexity of the full run can be reached for one implant evaluation at one position. Speed-up increases vastly with the number of evaluations. The presentation or final paper will also include investigations on changes in the HBM like variations of tissue properties or breathing.
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09:15-09:30, Paper ThAT20.6 | |
Dual-Applicator Microwave Ablation with Non-Parallel Antennas: Simulation and Experimental Evaluation (I) |
White, Austin | Kansas State Univ |
Prakash, Punit | Kansas State Univ |
Keywords: Image-guided devices - RF and microwave ablation, Image-guided devices - Interstitial thermal therapy, Computer modeling for treatment planning
Abstract: Image-guided microwave ablation is clinically used to treat tumors in the liver and other organs. When treating large tumors, physicians may use multiple antennas simultaneous to rapidly create large volume ablation zones Pre-clinical experimental and simulation studies to characterize ablation patterns created by multiple antennas often presume parallel antenna insertion, which may not be possible in clinical practice. We employed coupled electromagnetic – heat transfer simulations, incorporating temperature dependent tissue dielectric properties, to assess the impact of antenna misalignment on ablation zone profiles. Modeling results were validated with experiments in ex vivo liver tissue. For inter-antenna spacing in the range of 10 – 20 mm, the Dice Similarity Coefficient between parallel and non-parallel ablation zones ranged between 0.73 and 0.95.
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ThBT1 |
Meeting Room 311 |
Brain-Computer Interface - II (Theme 6) |
Oral Session |
Chair: Micera, Silvestro | Scuola Superiore Sant'Anna |
Co-Chair: Truccolo, Wilson | Brown Univ |
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10:00-10:15, Paper ThBT1.1 | |
Electroencephalography Classification in Brain-Computer Interface with Manifold Constraints Transfer |
Tan, Chuanqi | Tsinghua Univ |
Sun, Fuchun | Tsinghua Univ |
Zhang, Wenchang | Tsinghua Univ |
Kong, Tao | Tsinghua Univ |
Keywords: Brain-computer/machine interface, Neural signal processing, Neurorehabilitation
Abstract: Insufficient training data is a serious problem in all domains related to bioinformatics. Transfer learning is a promising tool to solve this problem, which relaxes the hypothesis that training data must be independent and identically distributed with the test data. We construct a sophisticated electroencephalography (EEG) signal representation and obtain an efficient EEG feature extractor through manifold constraints-based joint adversarial training with training data from other domains. EEG signal is more easily distinguished in the feature space mapped by the feature extractor. Negative transfer is one of the most challenging problems in transfer learning. In our approach, we apply manifold constraints to overcome this problem, which can avoid the geometric manifolds in the target domain being destroyed. The experiments demonstrate that our approach has many advantages when applied to EEG classification tasks.
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10:15-10:30, Paper ThBT1.2 | |
Development of a Cognitive Brain-Machine Interface Based on a Visual Imagery Method |
Koizumi, Koji | The Univ. of Tokyo |
Ueda, Kazutaka | The Univ. of Tokyo |
Nakao, Masayuki | Univ. of Tokyo |
Keywords: Brain-computer/machine interface, Human performance - Cognition, Brain functional imaging - EEG
Abstract: In the field of brain-machine interface (BMI) research, the development of cognitive BMI is a hot topic because it may lead to more intuitive and goal-directed findings than existing BMI technology. In this study, we devised a “visual-imagery method,” which enables visual imaging of the operation of a target. We also investigated an “inner-speech method,” which comprised internal pronunciation of words without emitting sounds, and an “inner-speech + visual-imagery method,” which combined the two methods. When only the high band (60-120 Hz) power in the prefrontal cortex was used, the average accuracy of the 15 participants, with 20-fold cross-validation, was 81.3% in inner speech, 84.6% in visual imagery, and 83.2% in inner speech + visual imagery. This study also found that the frontal pole was the most useful region in the prefrontal cortex.
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10:30-10:45, Paper ThBT1.3 | |
Spatiotemporal Characteristics of Cortical Activities Associated with Articulation of Speech Perception |
Saga, Naoki | Kobe Univ |
Yano, Hajime | Kobe Univ |
Takiguchi, Tetsuya | Kobe Univ |
Soeta, Yoshiharu | National Inst. of Advanced Industrial Science and Tech |
Nakagawa, Seiji | Chiba Univ |
Keywords: Brain-computer/machine interface, Brain functional imaging - MEG, Human performance - Cognition
Abstract: Recently, brain computer interface (BCI) technologies that control external devices with human brain signals have been developed. However, most of the BCI systems, such as P300-speller, can only discriminate among options that have been given in advance. Therefore, the ability to decode the state of a person's perception and recognition, as well as that person's fundamental intention and emotions, from cortical activity is needed to develop a more general-use BCI system. In this study, two experiments were conducted. First, articulations were measured for Japanese monosyllabic utterances masked by several levels of noise. Second, auditory brain magnetic fields evoked by the monosyllable stimuli used in the first experiment were recorded, and neuronal current sources were localized in regions associated with speech perception and recognition — the auditory cortex (BA41), the Wernicke's area (posterior part of BA22), Broca's area (BA22), motor (BA4), and premotor (BA6) areas. Although the source intensity did not systematically change with SNR, the peak latency changed along SNR in the posterior superior temporal gyrus in the right hemisphere. The results suggest that the information associated with articulation is processed in this area.
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10:45-11:00, Paper ThBT1.4 | |
FPGA Implementation of Deep-Learning Recurrent Neural Networks with Sub-Millisecond Real-Time Latency for BCI-Decoding of Large-Scale Neural Sensors (10^4 Nodes) |
Heelan, Christopher | Brown Univ |
Nurmikko, Arto | Brown Univ |
Truccolo, Wilson | Brown Univ |
Keywords: Brain-computer/machine interface, Neural signals - Coding
Abstract: Advances in neurotechnology are expected to provide access to thousands of neural channel recordings including neuronal spiking, multiunit activity and local field potentials. In addition, recent studies have shown that deep learning, in particular recurrent neural networks (RNNs), provide promising approaches for decoding of large-scale neural data. These approaches involve computationally intensive algorithms with millions of parameters. In this context, an important challenge in the application of neural decoding to next generation brain-computer interfaces for complex human tasks is the development of low-latency real-time implementations. We demonstrate a Field-Programmable Gate Array (FPGA) implementation of Long Short-Term Memory (LSTM) RNNs for decoding 10,000 channels of neural data on a mobile low-power embedded system platform called "NeuroCoder". We provide a proof of concept in the context of decoding 20-dimensional spectrotemporal representation of spoken words from simulated 10,000 neural channels. In this particular case, the LSTM model included 4,042,420 parameters. In addition to providing multiple communication interfaces for the BCI system, the NeuroCoder platform can achieve sub-millisecond real-time latencies.
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11:00-11:15, Paper ThBT1.5 | |
Effect of Implant Duration, Anatomical Location and Electrode Orientation on Bandwidth Recorded with a Chronically Implanted Stent-Electrode Array |
Opie, Nicholas | The Univ. of Melbourne |
John, Sam | Vascular Bionics Lab. the Department of Medicine, the Uni |
Rind, Gil | Vascular Bionics Lab. the Department of Medicine, the Uni |
Ronayne, Stephen | Vascular Bionics Lab. the Department of Medicine, the Uni |
May, Clive | Florey Inst. of Neuroscience and Mental Health |
Grayden, David B. | The Univ. of Melbourne |
Oxley, Thomas | Univ. of Melbourne |
Keywords: Brain-computer/machine interface, Motor neuroprostheses, Neurological disorders
Abstract: Access to the brain to implant recording electrodes has conventionally required a craniotomy. To mitigate risks of open brain surgery, we previously developed a stent-electrode array that can be delivered to the cortex via cerebral vessels. Following implantation of a stent-electrode array (Stentrode) in a large animal model, we investigated the longevity of high-quality signals, by measuring bandwidth in animals implanted for up to six months; no signal degradation was observed. We also investigated whether bandwidth was influenced by implant location with respect to the superior sagittal sinus and branching cortical veins; it was not. Finally, we assessed whether electrode orientation had an impact on recording quality. There was no significant difference in bandwidths from electrodes facing different orientations. Interestingly, electrodes facing the skull (180°) were still able to record neural information with high fidelity. Consequently, a minimally invasive surgical approach combined with a stent-electrode array is a safe and efficacious technique to acquire neural signals over a chronic duration.
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11:15-11:30, Paper ThBT1.6 | |
Increased Theta Oscillations During Motor Imagery in a Subject with Late-Stage ALS |
So, Rosa | Inst. for Infocomm Res |
Yang, Tao | Inst. of Infocomm Res |
Phua, Kok Soon | Inst. for Infocomm Res |
Yu, Juanhong | Inst. for Infocomm Res. And |
Toh, Valerie | National Neuroscience Inst |
Ng, Wai Hoe | National Neuroscience Inst |
Ang, Kai Keng | Inst. for Infocomm Res |
Keywords: Brain-computer/machine interface, Motor neuroprostheses, Neural signal processing
Abstract: Non-invasive brain computer interface (BCI) has been successfully used to control cursors, helicopters and robotic arms. However, this technology is not widely adopted by people with late-stage amyotrophic lateral sclerosis (ALS) due to poor effectiveness. In this study, we attempt to assess the cognitive state of a completely locked-in ALS subject, and her ability to use motor imagery-based BCI for control. The subject achieves above chance level accuracies for both open loop (62.2%) and closed-loop (68.7%) 2-class movement vs. idle decoding. We also observe a prominent theta oscillation with peak frequency at 4.5 Hz during the experiments. Quantification shows that the theta oscillatory power increases during motor imagery tasks compared to idle tasks for both open-loop as well as closed-loop BCI tasks. Furthermore, for closed-loop sessions, theta oscillation power correlates positively with feedback accuracy during movement tasks, and negatively with feedback accuracy during idle tasks. Our study demonstrates the feasibility of motor imagery-based BCI for late-stage ALS subjects, and highlights the importance of feedback during BCI implementation.
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ThBT2 |
Meeting Room 312 |
Data Mining for Biosignals (Theme 1) |
Oral Session |
Chair: Nguyen, Hung T. | Swinburne Univ. of Tech |
Co-Chair: Charbonnier, Sylvie | Gipsa-Lab |
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10:00-10:15, Paper ThBT2.1 | |
SSVEP Transient Feature Extraction and Rapid Recognition Method Based on Bistable Stochastic Resonance * |
Yao, Pulin | Xi'an Jiaotong Univ |
Xu, Guanghua | Xi'an Jiaotong Univ |
Han, Chengcheng | Xi’an Jiaotong Univ |
Zhang, Sicong | Xi’an Jiaotong Univ |
Luo, Ailing | Xi’an Jiaotong Univ |
Zhang, Qing | Xi'an JIaotong Univ |
Keywords: Data mining and processing - Pattern recognition
Abstract: Steady-state Visual Evoked Potentials, SSVEP), as the most commonly used communication paradigm for non-implantable Brain-Computer Interface (BCI), boasts the advantages of no training, noise immunity and obvious periodicity. The traditional SSVEP extraction methods can effectively identify the target frequency contained in original EEG, however, the required data length usually lasts a few seconds. In this paper, bistable stochastic resonance (BSR) is applied to SSVEP extraction. BSR is very sensitive to amplitude mutation and frequency fluctuation of the input signal, making the output difference can be used for the detection of the target frequency. The processing results illustrate that the proposed method not only has a high recognition accuracy, but also effectively shortens the recognition time, thus improving the calculating speed. Therefore, SSVEP Extraction has a higher information transfer rate (ITR) based on bistable stochastic resonance, which is more suitable for the real-time BCI system.
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10:15-10:30, Paper ThBT2.2 | |
A Multi-Feature Fuzzy Index to Assess Stress Level from Bio-Signals |
Charbonnier, Sylvie | Gipsa-Lab |
Vila, Gael | CEA/LETI |
Godin, Christelle | CEA/LETI |
Labyt, Etienne | CEA/LETI/CLINATEC |
Sakri, Oumayma | CEA/LETI |
Campagne, Aurélie | Lab. De Psychologie Et Neurocognition, Grenoble |
Keywords: Data mining and processing in biosignals
Abstract: A mono-feature fuzzy index that evaluates the stress level from one feature extracted from ECG or GSR is presented. It is build using several measures of the feature recorded when the subject is at rest. The mono-feature fuzzy index can be merged in a multi-feature stress index without any tuning. It can be used to select relevant features and to detect stress. The performance of the stress index is analyzed on a data set made of 160 time periods of time when 20 subjects had to perform stressful tasks and corresponding control tasks. The stress was induced by 4 different tasks. The performances reached are 72% of correctly classified time periods in stress and no stress situations. Interesting conclusions could also be made on the tasks ability to induce stress.
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10:30-10:45, Paper ThBT2.3 | |
Automatic Detection of Hot Flash Occurrence and Timing from Skin Conductance Activity |
Forouzanfar, Mohamad | Stanford Univ |
de Zambotti, Massimiliano | SRI International |
Goldstone, Aimée | SRI International |
Baker, Fiona | SRI International |
Keywords: Data mining and processing in biosignals, Signal pattern classification, Physiological systems modeling - Signal processing in physiological systems
Abstract: Hot flashes (HF) are intense, transient feelings of heat usually accompanied with flushed skin and sweating that are experienced by women around the time of menopause. HFs are associated with poor quality of life and increased cardiovascular risk. Automatic detection of HF occurrence and precise timing of HF onset could provide unique insight into the physiology of the HF and its effect on the cardiovascular system. A novel automatic algorithm is proposed for the detection of HFs occurrence and timing from the sternal skin conductance signal that is robust to noise and artifacts. The method is based on the gold standard rule (2 μS rise in skin conductance within 30 s) and considers several conditions based on the skin conductance level and its derivative to reject unwanted events. ECG-derived heart rate pattern variations are studied prior to the detected HF onset. The algorithm is validated against expert detected HFs over 200 hours of sleep data collected from 12 perimenopausal women. It achieved a total accuracy of 93% and a total error of 3% in HF detection. It was observed that heart rate increased before the onset of 80% of the HFs occurring in undisturbed sleep. Application of this algorithm along with fusion of other simultaneously recorded physiological measures has the potential to advance understanding of the HF.
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10:45-11:00, Paper ThBT2.4 | |
Gated Recurrent Neural Networks for EMG-Based Hand Gesture Classification: A Comparative Study |
Samadani, Ali | Philips Res. North America |
Keywords: Data mining and processing - Pattern recognition, Neural networks and support vector machines in biosignal processing and classification, Signal pattern classification
Abstract: Electromyographic activities (EMG) generated during contraction of upper limb muscles can be mapped to distinct hand gestures and movements, posing them as a promising modality for prosthetic and cybernetic applications. This paper presents a comparative analysis between different recurrent neural network (RNN) configurations for EMG-based hand gesture classification. In particular, RNNs with recurrent units of long short-term memory (LSTM) and gated recurrent unit (GRU) are evaluated. Furthermore, the effects of an attention mechanism and varying learning rates are evaluated. Results show a classifier 1)~with a bidirectional recurrent layer composed of LSTM units, 2)~that applies the attention mechanism, and 3)~trained with step-wise learning rate outperforms all other tested RNN classifiers.
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11:00-11:15, Paper ThBT2.5 | |
Quantitative Assessment of Cerebellar Ataxia with Kinematic Sensing During Rhythmic Tapping |
Nguyen, Khoa Dinh | Deakin Univ |
Pathirana, Pubudu N. | Deakin Univ |
Horne, Malcolm | Florey Inst. of Neuroscience and Mental Health |
Power, Laura | Royal Victorian Eye and Ear Hospital |
Szmulewicz, David | Victorian Eye and Ear Hospital |
Keywords: Data mining and processing in biosignals, Signal pattern classification
Abstract: The aim of this study is to investigate the validity of an entropy-based objective assessment of cerebellar ataxia patients performing rhythmic tapping. Previous research conducted, particularly in time and frequency domains, tested the adherence of patients to more stringent experimental requirements. These requirements may inadvertently cause higher level brain functions to influence the performance and possibly obscure the cerebella related disabilities in the data stream. In this study, a multiscale entropy-based learning process that overcomes this practical limitation was considered. In particular, assessment techniques with less restrictions on the tapping duration were considered. Thirty-three patients were engaged in the test, with three levels of severity 0 (normal), 1 (moderate) and 2 (severe) ranked by specialist clinicians. The performance of each model was evaluated using leave-one-out cross validation. Results from both time-frequency features and entropy features extracted and characterized the cerebellar condition captured during the finger and foot tapping tests (with over 80% accuracy). Strong correlations with clinical assessment-based scoring were observed with the entropy based approach for both tests, although the correlation with time-frequency features were less convincing.
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11:15-11:30, Paper ThBT2.6 | |
Study of Compressed Sensing and Predictor Techniques for the Compression of Neural Signals under the Influence of Noise |
Pagin, Matteo | Univ. of Ulm |
Ortmanns, Maurits | Univ. of Ulm |
Keywords: Data mining and processing in biosignals
Abstract: In this paper an analysis of compression schemes based on compressed sensing (CS) and predictor techniques for neural signals is presented. The focus is on how much a compression algorithm can reduce data while not affecting the subsequent signal processing. Since neural signals are processed by means of spike sorting algorithms the evaluation is not trivial and not well defined, since there exists in fact many different ways to detect and cluster the spikes. Evaluating how much a compression scheme affects the result of spike sorting programs is a crucial step before implementing such compression technique. In the analysis two use cases are evaluated: in the first, spikes are detected and extracted and only thereafter compressed. In the second case, no information on the spikes is available and the whole raw signal is compressed. When dealing only with spike frames CS offers great compression at almost no loss, in the case of the whole recording its performances are greatly impaired and delta compression outperforms it in terms of data reduction and spike sorting results. In this case the reduction rates are modest but significant, ≈3-4 times data reduction and the whole signal is preserved avoiding big permanent losses of information.
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ThBT3 |
Meeting Room 314 |
Cardiac Imaging (I) (Theme 2) |
Oral Session |
Chair: Suzuki, Kenji | Illinois Inst. of Tech |
Co-Chair: Punithakumar, Kumaradevan | Univ. of Alberta |
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10:00-10:15, Paper ThBT3.1 | |
Motion Tracking for Beating Heart Based on Sparse Statistic Pose Modeling |
Yang, Bo | Univ. of Electronic Science and Tech. of China |
Cao, Tingting | Univ. of Electronic Science and Tech. of China |
Zheng, Wenfeng | Univ. of Electronic Science and Tech. of China |
Liu, Shan | Univ. of Electronic Science and Tech. of China |
Keywords: Image reconstruction - Performance evaluation, Image reconstruction - Fast algorithms, Iterative image reconstruction
Abstract: A novel region-based method to track beating heart is proposed. Sparse statistical pose modeling is used to reconstruct the region of interest (ROI) on beating heart surface. Firstly, a high-complexity thin plate spline is employed to pre-reconstructed the ROI of a series of frames. The 3D pose data of the ROI from the pre-reconstructed results are extracted to train a low-complexity model based on the sparse statistical analysis. The new trained low-complexity model is robust and efficient for ROI reconstruction of the following frames. The proposed model significantly reduces the redundant degrees of freedom to fit the surface of the heart. A constraint item is added to the objective function which describes the 3D tracking problem to avoid erroneous convergence of the efficient second-order minimization (ESM) optimization algorithm. The proposed method is evaluated on the phantom heart video and the in vivo video obtained by the da Vinci surgical system.
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10:15-10:30, Paper ThBT3.2 | |
Image Data Analysis for Quantifying Scar Transmurality in MRI Phantoms for Cardiac Resynchronisation Therapy |
Karim, Rashed | King's Coll. London |
Panayiotou, Maria | King's Coll. London |
Chowdhury, Onik | Chool of Biomedical Engineering & Imaging Sciences, King’s Coll |
Housden, Richard James | King's Coll. London |
Hummady, Sana | Siemens Healthineers |
Toth, Daniel | King’s Coll. London, UK |
Kurzendorfer, Tanja | Friedrich-Alexander Univ. Erlangen-Nuremberg |
Mountney, Peter | Siemens |
Rhode, Kawal | King's Coll. London |
Keywords: Cardiac imaging and image analysis, Magnetic resonance imaging - Cardiac imaging, Magnetic resonance imaging - Dynamic contrast-enhanced MRI
Abstract: The use of implantable cardiac devices has in- creased in the last 30 years. Cardiac resynchronisation therapy (CRT) is a procedure which involves implanting a coin sized pacemaker for reversing heart failure. The pacemaker electrode leads are implanted into cardiac myocardial tissue. The optimal site for implantation is highly patient-specific. Most implanters use empirical placement of the lead. One region identified to have a poor response rate are myocardial tissue with transmural scar. Studies that precisely measure transmurality of scar tissue in the left ventricle (LV) are few. Most studies lack proper validation of their transmurality measurement technique. This study presents an image analysis technique for computing scar transmurality from late-gadolinium enhancement MRI. The technique is validated using phantoms under a CRT image guidance system. The study concludes that scar transmurality can be accurately measured in certain situations and validation with phantoms is important.
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10:30-10:45, Paper ThBT3.3 | |
Comparison of Image Acquisition Techniques in Four-Dimensional Flow Cardiovascular MR on 3 Tesla in Volunteers and Tetralogy of Fallot Patients |
Zhang, Jun-Mei | National Heart Center |
tan, ru san | National Heart Center |
Zhang, Shuo | Philips |
van der Geest, Rob | Leiden Univ. Medical Center |
Garg, Pankaj | Univ. of Leeds |
Leong, Bao Ru | National Heart Centre Singapore |
Bryant, Jennifer | NHCS |
Tangcharoen, Tarinee | Ramathibodi Hospital, Mahidol Univ |
Zhao, Xiaodan | National Heart Centre Singapore |
Tan, Ju Le | National Heart Centre Singapore |
Westenberg, Jos | Leiden Univ. Medical Center |
Zhong, Liang | National Heart Centre Singapore |
Keywords: Magnetic resonance imaging - Cardiac imaging, Magnetic resonance imaging - Pulse sequence, Cardiac imaging and image analysis
Abstract: Four-dimensional phase-contrast (PC) velocity-encoded flow magnetic resonance imaging (4D flow MRI) is a potentially valuable tool for studying cardiovascular hemodynamics for disease monitoring and/or treatment planning. In this study we compared the performance of two 4D flow MRI pulse sequences - echo-planar imaging (EPI) and segmented gradient-echo (turbo-field-echo or TFE on vendor’s platform) - on a clinical 3T system in 6 human subjects including 3 patients with Tetralogy of Fallot (TOF). For aortic flow rate, the coefficients of variation (COV) between 2D and 4D EPI were 7.0% and 7.7% for controls and patients respectively. The corresponding COV between 2D and 4D TFE were 19.0% and 18.3% for controls and patients respectively. The COV between 4D TFE and 4D EPI were larger than 18.7% in kinetic energy analysis. 4D EPI demonstrated acceptable accuracy of intra-cardiac flow quantification, which was also shown in the ex-vivo phantom measurements.
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10:45-11:00, Paper ThBT3.4 | |
A Novel 4D Semi-Automated Algorithm for Volumetric Segmentation in Echocardiography |
Krishnaswamy, Deepa | Univ. of Alberta |
Rakkunedeth Hareendranathan, Abhilash | Univ. of Alberta |
Suwatanaviroj, Tan | Mazankowski Alberta Heart Inst. Univ. of Alberta, Edmo |
Boulanger, Pierre | Univ. of Alberta |
Becher, Harald | Mazankowski Alberta Heart Inst. Univ. of Alberta, Edmo |
Noga, Michelle | Univ. of Alberta |
Punithakumar, Kumaradevan | Univ. of Alberta |
Keywords: Image segmentation, Ultrasound imaging - Cardiac, Cardiac imaging and image analysis
Abstract: Segmentation of the left ventricle (LV) in temporal 3D echocardiography sequences poses a challenge. However, it is an essential component in generating quantitative clinical measurements for the diagnosis and treatment of various cardiac diseases. Identifying the endocardial borders of the left ventricle can be difficult due to the inherent properties of ultrasound. This study proposes a 4D segmentation algorithm that segments over temporal 3D volumes that has minimal user interaction and is based on a diffeomorphic registration approach. In contrast to several existing algorithms, the proposed method does not depend on training data or make any geometrical assumptions. The algorithm was evaluated on seven patients obtained from the Mazankowski Alberta Heart Institute, Edmonton, Canada in comparison to expert manual segmentation. The proposed approach yielded Dice scores of 0.94 (0.01), 0.91 (0.03) and 0.92 (0.02) at end diastole, at end systole and over the entire cardiac cycle, respectively. The corresponding Hausdorff distance values were 4.49 (1.01) mm, 4.94 (1.41) mm, and 5.05 (0.85) mm, respectively. These results demonstrate that the proposed 4D segmentation approach for the left ventricle is robust and can potentially be used in clinical practice.
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11:00-11:15, Paper ThBT3.5 | |
Multiview Sequential Learning and Dilated Residual Learning for a Fully Automatic Delineation of the Left Atrium and Pulmonary Veins from Late Gadolinium-Enhanced Cardiac MRI Images |
Yang, Guang | Imperial Coll. London |
Chen, Jun | Shenzhen Inst. of Advanced Tech. Chinese Acad. of S |
Gao, Zhifan | Shenzhen Inst. of Advanced Tech. Chinese Acad. of S |
Zhang, Heye | Hong Kong Univ. of Science & Tech |
Ni, Hao | Univ. Coll. London |
Angelini, Elsa | Imperial NIHR BRC, Imperial Coll. London |
Mohiaddin, Raad | Imperial Coll. London |
Wong, Tom | Imperial Coll. London |
Keegan, Jennifer | Imperial Coll. London |
Firmin, David | Imperial Coll. London |
Keywords: Image registration, segmentation, compression and visualization - Machine learning / Deep learning approaches, Cardiac imaging and image analysis, Magnetic resonance imaging - Cardiac imaging
Abstract: Accurate delineation of heart substructures is a prerequisite for abnormality detection, for making quantitative and functional measurements, and for computer-aided diagnosis and treatment planning. Late Gadolinium-Enhanced Cardiac MRI (LGE-CMRI) is an emerging imaging technology for myocardial infarction or scar detection based on the differences in the volume of residual gadolinium distribution between scar and healthy tissues. While LGE-CMRI is a well-established non-invasive tool for detecting myocardial scar tissues in the ventricles, its application to left atrium (LA) imaging is more challenging due to its very thin wall of the LA and poor quality images, which may be produced because of motion artefacts and low signal-to-noise ratio. As the LGE-CMRI scan is designed to highlight scar tissues by altering the gadolinium kinetics, the anatomy among different heart substructures has less distinguishable boundaries. An accurate, robust and reproducible method for LA segmentation is highly in demand because it can not only provide valuable information of the heart function but also be helpful for the further delineation of scar tissue and measuring the scar percentage. In this study, we proposed a novel deep learning framework working on LGE-CMRI images directly by combining sequential learning and dilated residual learning to delineate LA and pulmonary veins fully automatically. The achieved results showed accurate segmentation results compared to the state-of-the-art methods. The proposed framework leads to an automatic generation of a patient-specific model that can potentially enable an objective atrial scarring assessment for the atrial fibrillation patients.
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11:15-11:30, Paper ThBT3.6 | |
Improving Visual Detection of Wall Motion Abnormality with Echocardiographic Image Enhancing Methods |
Omar, Hasmila | Oxford Univ |
Domingos, Joao | Univ. of Oxford |
Patra, Arijit | Oxford Univ |
Leeson, Paul | John Radcliffe Hospital |
Noble, J Alison | Univ. of Oxford |
Keywords: Ultrasound imaging - Cardiac, Image enhancement, Cardiac imaging and image analysis
Abstract: Analysis of wall motion abnormality using echocardiography is an established method for detecting myocardial ischemia. We describe a hybrid approach of enhancing 2D+T echo datasets with border detection and Eulerian motion magnification to improve the visual assessment of wall motion. We implemented a local phase-based approach using the monogenic signal and its derived features, either feature asymmetry (FA) or oriented feature symmetry (OFS), to detect boundaries of the heart structure. We enhanced the 2D+T datasets using either an intensity-based or phase-based Eulerian Motion Magnification (EMM) video processing technique, and identified among eight different types of enhancements the best performing method as OFS with an accuracy of 78% versus the original B-Mode with an accuracy of 71%.
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ThBT4 |
Meeting Room 315 |
Minisymposia: Recent Innovations and New Health-Related Applications of
Electrical Bioimpedance (3662q) |
Minisymposium |
Chair: Sanchez, Benjamin | Harvard Medical School |
Co-Chair: Freeborn, Todd | Univ. of Alabama |
Organizer: Halter, Ryan | Dartmouth Coll |
Organizer: Inan, Omer | Georgia Inst. of Tech |
Organizer: Woo, Eung Je | Kyung Hee Univ |
Organizer: Freeborn, Todd | Univ. of Alabama |
Organizer: Sanchez, Benjamin | Harvard Medical School |
Organizer: Rutkove, Seward | Harvard Medical School |
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10:00-10:15, Paper ThBT4.1 | |
Applying Localized Electrical Bioimpedance for Monitoring Exercise-Induced Fatigue (I) |
Freeborn, Todd | Univ. of Alabama |
Keywords: Clinical engineering, Diagnostic devices - Physiological monitoring, Health technology management and assessment
Abstract: Localized electrical bioimpedance measurements quantify the passive electrical properties of a tissue. Recently bioimpedance methods have been investigated as a technique to monitor localized tissues for changes from the contraction and fatigue of skeletal muscle. The positive results from these studies support the further investigation and application of this technique to quantify exercise-induced changes in bioimpedance as a marker for fatigue status and recovery from fatigue.
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10:15-10:30, Paper ThBT4.2 | |
Multimodal Electrical Impedance Tomography (EIT): Advances in EIT-Coupled Ultrasound Imaging (I) |
Halter, Ryan | Dartmouth Coll |
Keywords: Diagnostic devices - Physiological monitoring, Image-guided devices - Biopsy
Abstract: Electrical Impedance Tomography (EIT) maps the electrical properties of biological systems. While the resolution of this modality is somewhat limited, it provides high levels of sensitivity and specificity in terms of pathology identification and assessment. By coupling EIT with ultrasound (US) as a multi-modal imaging system one can achieve higher resolution electrical property imaging with more sensitivity and specificity than US alone. Multiple approaches to implementing EIT-coupled US imaging are possible including geometric constrained, hard-prior, and soft-prior imaging.
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10:30-10:45, Paper ThBT4.3 | |
Clinical Applications of EIT in Pulmonary Medicine (I) |
Woo, Eung Je | Kyung Hee Univ |
OH, TONG IN | Kyunghee Univ |
Wi, Hun | KyungHee Univ |
Keywords: Diagnostic devices - Physiological monitoring, Wearable or portable devices for vital signal monitoring
Abstract: Electrical impedance tomography (EIT) has shown a great potential as a new portable real-time imaging modality in lung imaging. Most previous studies have focused on regional lung ventilation imaging during mechanical ventilation. We proposed two new clinical applications of EIT in pulmonary medicine including obstructive sleep apnea (OSA) diagnosis and pulmonary function test (PFT). In this paper, we report our latest experimental results of these two topics. The application of EIT for OSA diagnosis was tested in a series experimental studies where lung EIT and polysomnography (PSG) were simultaneously performed. For the application in PFT, we combined an existing spirometer with our lung EIT device as a spirotomometer. Preliminary experimental results are promising and suggest further clinical studies.
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10:45-11:00, Paper ThBT4.4 | |
Wearable Electrical Bioimpedance for Detecting Joint Edema (I) |
Hersek, Sinan | Georgia Inst. of Tech |
Mabrouk, Samer | Georgia Inst. of Tech |
Inan, Omer | Georgia Inst. of Tech |
Keywords: Wearable or portable devices for vital signal monitoring, Diagnostic devices - Physiological monitoring
Abstract: This minisymposium contribution focuses on our ongoing studies focused on using electrical bioimpedance (EBI) to detect edema in joints. The ultimate goal is to incorporate EBI sensing into a wearable brace, such that joint edema levels can be longitudinally monitored by patients at home. This could provide benefit, for example, to patients rehabilitating acute knee injuries, delivering quantitative feedback on the healing progress such that therapies and rehabilitation protocols can be adjusted based on changing patient needs. We have performed experiments in human subjects with acute knee injuries and compared the EBI measures between the injured and contralateral side, demonstrating that significant changes exist due to fluid accumulation on the injured side. In this contribution, we also present results of a study performed in a pig limb, with small amounts of saline (2-10 mL) infused into the limb and detected effectively by the EBI hardware.
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ThBT5 |
Meeting Room 316A |
Invited Session: Machine Learning / Deep Learning for Medical Image
Analysis (85dkb) |
Invited Session |
Chair: Gonzalez Ballester, Miguel Angel | ICREA & Univ. Pompeu Fabra |
Co-Chair: Schnabel, Julia | King's Coll. London |
Organizer: Gonzalez Ballester, Miguel Angel | ICREA & Univ. Pompeu Fabra |
Organizer: Schnabel, Julia | King's Coll. London |
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10:00-10:15, Paper ThBT5.1 | |
Deep Learning for Image Reconstruction and Super-Resolution: Applications in Cardiac MR Imaging (I) |
Schlemper, Jo | Imperial Coll. London |
Oktay, Ozan | Imperial Coll. London |
Rueckert, Daniel | Imperial Coll. London |
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10:15-10:30, Paper ThBT5.2 | |
Machine Learning for Cancer Imaging (I) |
Schnabel, Julia | King's Coll. London |
Bates, Russell | Univ. of Oxford |
Grau, Vicente | Univ. of Oxford |
Brady, Michael | Univ. of Oxford |
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10:30-10:45, Paper ThBT5.3 | |
Machine Learning for Medical Image Analysis and Decision Support in Cardiology, Neurodegenerative Diseases and Fetal Surgery (I) |
Gonzalez Ballester, Miguel Angel | ICREA & Univ. Pompeu Fabra |
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10:45-11:00, Paper ThBT5.4 | |
Deep Learning for Cardiovascular CT Analysis (I) |
Isgum, Ivana | Univ. Medical Center Utrecht |
Wolterink, Jelmer Maarten | Univ. Medical Center Utrecht |
de Vos, Bob D. | UMCU |
Lessmann, Nikolas | UMC Utrecht |
Zreik, Majd | Univ. Medical Center Utrecht |
van Velzen, Sanne G. M. | Univ. Medical Center Utrecht |
de Jong, Pim A | Univ. Medical Center Utrecht |
Leiner, Tim | Univ. Medical Center Utrecht |
Viergever, Max A. | Univ. Medical Center Utrecht |
Keywords: Cardiac imaging and image analysis, Image segmentation, CT imaging
Abstract: In this presentation, we will demonstrate applications of deep learning methods for cardiovascular CT image analysis. We will focus on segmentation and quantification for cardiovascular risk determination in CT scans as a requested or unrequested finding. Furthermore, we will show an application of generative deep learning that allows determination of cardiovascular risk in CT images acquired with very low radiation dose. Finally, we will show how a combination of conventional machine learning and deep learning can be used to detect functionally significant coronary artery stenosis in CT angiography scans.
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11:00-11:15, Paper ThBT5.5 | |
Transfer Learning for Biomedical Image Analysis across Scanners (I) |
de Bruijne, Marleen | Erasmus MC - Univ. Medical Center Rotterdam |
Keywords: Image analysis and classification - Machine learning / Deep learning approaches
Abstract: Machine learning techniques generally assume that the training data that is used to learn model parameters is representative of the target data to analyze. If this assumption does not hold, performance will deteriorate. For machine learning in medical imaging this means that accuracy may decrease when training data is acquired at another hospital, with a different scanner, with slightly different scan parameters, or from a different patient population. In this talk, we will provide an overview of techniques to compensate for differences between train and target data. We demonstrate how these transfer learning techniques improve accuracy across scanners for a range of applications in medical image analysis.
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ThBT6 |
Meeting Room 316B |
Invited Session: ARTIFICIAL VISION: LATEST PROGRESS AND CHALLENGES AHEAD
(58q8k) |
Invited Session |
Chair: Fried, Shelley | Massachusetts General Hospital / Harvard Medical School |
Co-Chair: CHAN, Leanne LH | City Univ. of Hong Kong |
Organizer: Fried, Shelley | Massachusetts General Hospital / Harvard Medical School |
Organizer: CHAN, Leanne LH | City Univ. of Hong Kong |
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10:00-10:15, Paper ThBT6.1 | |
Progress in Photovoltaic Restoration of Sight (I) |
Palanker, Daniel | Stanford Univ |
Lorach, Henri | Stanford Univ |
Kamins, Ted | Stanford Univ |
Mathieson, Keith | Univ. of Strathclyde |
Sher, Alexander | UC Santa Cruz |
Flores, Thomas | Stanford Univ |
Keywords: Sensory neuroprostheses - Visual, Neural interfaces - Implantable systems, Neural interfaces - Tissue-electrode interface
Abstract: Photovoltaic subretinal prosthesis converts light into electric current, stimulating the nearby inner retinal neurons. Visual information is projected onto the implant by video goggles using pulsed near-infrared (880-915nm) light. Such design avoids the need for bulky electronics and wires, thereby greatly reducing the surgical complexity, and allows scaling the number of pixels to thousands. Like in normal vision, retinal response to prosthetic stimulation exhibits flicker fusion at high frequencies (>20 Hz), adaptation to static images, antagonistic center-surround organization, and non-linear summation of subunits in the RGCs receptive fields, providing much higher spatial resolution than the average size of receptive fields. Such implants elicited responses to both onset and offset of light, with approximately 1/6th of the natural contrast sensitivity. Photovoltaic arrays with 55um pixels implanted in blind rats restored a grating visual acuity up to the pixel pitch. If these results translate to human retina, such implants could restore visual acuity up to 20/200. Higher resolution may be achieved utilizing 3-dimensional electro-neural interfaces.
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10:15-10:30, Paper ThBT6.2 | |
Visual and Electric Spiking Signatures of Seven Types of Rabbit Retinal Ganglion Cells (I) |
Werginz, Paul | Massachusetts General Hospital / Harvard Medical School |
Im, Maesoon | Henry Ford Health System |
Hadjinicolaou, Alex E. | Australian Coll. of Optometry |
Fried, Shelley | Massachusetts General Hospital / Harvard Medical School |
Keywords: Neural stimulation, Sensory neuroprostheses - Visual
Abstract: Electric stimulation of the retina via retinal implants is currently the only commercially available method to restore vision in patients suffering from a wide range of outer retinal degenerations. To improve the quality of retinal implants, it is desirable to better understand how different retinal cell classes and types respond to electric stimuli so that more effective stimulation strategies can be developed. Here, we measured the response of seven major types of retinal ganglion cells to electric stimulation. A simple series of light stimuli were used to classify cells into known types. Electric stimulation produced unique responses in most ganglion cell types and the responses typically matched elements of the corresponding light responses.
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10:30-10:45, Paper ThBT6.3 | |
Optimizing the Performance of Retinal Neuroprostheses with High-Frequency Electrical Stimulation (I) |
Lovell, Nigel H. | Univ. of New South Wales |
Guo, Tianruo | Univ. of New South Wales |
Dokos, Socrates | Univ. of New South Wales |
Suaning, Gregg | The Univ. of Sydney |
Morley, John William | Univ. of Western Sydney |
Keywords: Neural stimulation, Sensory neuroprostheses - Visual
Abstract: Recent retinal studies have demonstrated the ability to differentially recruit ON and OFF retinal ganglion cells (RGCs), using high frequency stimulation (HFS). By a combination of in vitro experiments and computational models we further investigated whether preferential excitation of ON and OFF RGCs can be optimized through a combination of stimulation parameters and stimulus electrode location relative to the axon initial segment (AIS) and axon direction. Stimulation parameters investigated included HFS pulse amplitude and HFS pulse train frequency.
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10:45-11:00, Paper ThBT6.4 | |
Selective Stimulation of the Retina for Improved Acuity (I) |
Weiland, James | Univ. of Michigan |
Chang, Yao-Chuan | Univ. of Southern California |
Weitz, Andrew | Univ. of Southern California |
Chow, Robert | Univ. of Southern California |
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11:00-11:15, Paper ThBT6.5 | |
Voltage-Sensitive Dye Neural Imaging for Testing and Designing Stimuli in Visual Prostheses (I) |
Hayashida, Yuki | Osaka Univ |
Keywords: Sensory neuroprostheses - Visual, Neural stimulation, Sensory neuroprostheses
Abstract: In recent years, we have been utilizing the voltage-sensitive dye (VSD) imaging technique to measure the neural responses to microstimulation in the visual cortical areas of rodents in vivo, and in the slice preparations in vitro. These imaging experiments enable us to estimate, for example, the threshold and saturation charges for a single stimulus pulse to induce neural excitation in the immediate vicinity of the stimulating electrode, or the spatial extent of population spike initiated within a few milliseconds after the stimulus onset. Therefore, the VSD imaging is thought to be useful to gain insight into the design of safe and efficacious stimulation strategy for neural prostheses.
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11:15-11:30, Paper ThBT6.6 | |
Retinal Neuromodulation and the Neural Code - Lost in Translation? (I) |
Suaning, Gregg | The Univ. of Sydney |
Morley, John William | Univ. of Western Sydney |
Lovell, Nigel H. | Univ. of New South Wales |
Guo, Tianruo | Univ. of New South Wales |
Dokos, Socrates | Univ. of New South Wales |
Barriga-Rivera, Alejandro | Univ. Pablo De Olavide |
Keywords: Sensory neuroprostheses - Visual, Neural interfaces - Implantable systems, Neural stimulation
Abstract: Deaf children fitted with cochlear implants now attend mainstream schools and lead lives as part of the hearing world; artificial limbs have achieved Olympic caliber performance; and, more recently, the profoundly blind are capturing their first glimpses of what the future will bring through retinal neuroprosthesis technologies. While it is tempting to say, ‘mission accomplished’, there remains an enormous gap between natural and artificially-modulated neural activity. A key element in our quest towards making artificial neuromodulation more natural is the unlocking of the neural code – that is, the elicitation of neural firing that describes what we hear, how we should move, and how we see. The spatial and temporal constituents of this code are only now being exploited to improve outcomes. Here we describe our work towards unlocking of the neural code for the restoration of vision.
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ThBT7 |
Meeting Room 316C |
Minisymposia: ROBOTIC NEUROREHABILITATION: THE STATE-OF-SCIENCE (m228a) |
Minisymposium |
Chair: Patton, James | U. Illinois at Chicago (UIC), & the Shirley Ryan Ability Lab (formerly RIC) |
Co-Chair: Rymer, William Zev | Northwest. & Rehab Inst. of Chicago |
Organizer: Patton, James | U. Illinois at Chicago (UIC), & the Shirley Ryan Ability Lab (formerly RIC) |
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10:00-10:15, Paper ThBT7.1 | |
Rehabilitation, Personal Mobility & Recreation with Wearable Exoskeletons (I) |
Jayaraman, Arun | Rehabilitation Inst. of Chicago and Northwestern Univ |
Rymer, William Zev | Northwest. & Rehab Inst. of Chicago |
Keywords: Rehabilitation robotics and biomechanics - Exoskeleton robotics, Biomechanics and robotics - Clinical evaluation in rehabilitation and orthopedics, Assistive and cognitive robotics in rehabilitation
Abstract: Abstract— This talk will provide a short overview of Robotic exoskeletons and how they are used in different fields for enhancing human locomotion. Wearable robotics, specifically robotic exoskeletons research that has gained substantial attention in recent years. Interestingly, the acceptance of these devices into everyday clinical practice and home use is still limited by past and present research. Currently, there exists a void between the research evidence and clinical evidence on the predicated utility and actual usability of wearable robotic systems. Our talk will discuss on how engineering and clinical science can be combined and performed simultaneously and sequentially to gain insight to clinical utility of wearable robots to specific clinical populations and to understand the needed continued adaptations in the hardware and controller mechanisms of these devices when they are used in disabled populations who struggle with differential muscle weakness, range of motion limitations, cognitive disabilities, variable balance and altered neuromotor control. We will discuss how specific wearable robots can be used to target specific populations and how they provide clinical benefits. Additionally, we will talk about training strategies and complexities to consider when training individuals with varying disabilities to take these devices as personal mobility devices home. Finally, we will discuss how robotic exoskeletons can be transitioned to being used as recreational or performance augmentation devices in everyday life. This information will help clinicians and scientists gain some additional insight into how these eloquent technologies can be seamlessly transitioned further into the field of rehabilitation.
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10:15-10:30, Paper ThBT7.2 | |
Using Technology to Alter Hand Activation Patterns after Stroke (I) |
Kamper, Derek | North Carolina State Univ |
Barry, Alexander | Shirley Ryan AbilityLab |
Triandafilou, Kristen M. | Rehabilitation Inst. of Chicago |
Ghassemi, Mohammad | North Carolina State Univ |
Roth, Elliot | Rehabilitation Inst. of Chicago |
Keywords: Therapeutic robotics in rehabilitation, Wearable robotic systems - Orthotics
Abstract: Sensorimotor impairment after stroke presents a multifaceted challenge for recovery. By combining robotic technologies with other treatment modalities, a holistic approach can be advanced to address a range of impairment mechanisms. We are conducting an ongoing clinical trial in which a pharmacological agent, cyproheptadine, is administered in conjunction with training of muscle activation patterns through custom, electromyographically controlled orthoses and computer games.
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10:30-10:45, Paper ThBT7.3 | |
Compelling the Nervous System into Recovering (I) |
Brown, David | UAB |
Keywords: Biomechanics and robotics - Clinical evaluation in rehabilitation and orthopedics, Rehabilitation robotics and biomechanics - Devices and methods for assessment and therapy in infancy
Abstract: How can rehabilitation clinicians take advantage of new technologies to help individuals improve movement function after neurologic injury? People recovering from nervous system disease or injury are faced with many constraints in terms of how to use remaining neural resources to recover functional movement. In particular, people post-stroke are faced with loss of corticofugal fibers that can recruit and drive interneuronal and motoneuronal circuits in a coordinated and effective manner that results in successful movement tasks. Remaining circuits may allow for alternate pathways to be recruited, so the potential exists for improved movement patterns, even under the constraints imposed by lost input pathways. Collaborative robots allow an interaction between the patient and the machine so that the patient can be challenged by the machine and the machine can respond to the patient’s movements to provide clear feedback about success or failure of a given task. We have used a collaborative robotic system, The KineAssist, to develop an approach to clinical testing and training that takes advantage of the specific biomechanical requirements of individual movement tasks in order to measure the highest performance capacity of a task and then use that measurement to personalize a training regimen designed to expand that highest performance capacity.
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10:45-11:00, Paper ThBT7.4 | |
Complementary Technology to Support Human Locomotion (I) |
Vallery, Heike | TU Delft |
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11:00-11:15, Paper ThBT7.5 | |
Deceiving the Nervous System into Recovering (I) |
Patton, James | U. Illinois at Chicago (UIC), & the Shirley Ryan Ability Lab (fo |
Huang, Felix | Rehabilitation Inst. of Chicago |
Wright, Zachary | Univ. of Illinois at Chicago, Rehabilitation Inst. of C |
Parmar, Pritesh | Univ. of Illinois |
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ThBT8 |
Meeting Room 318A |
Invited Session: Wearable EEG for Real-Life Brain Monitoring (b2411) |
Invited Session |
Chair: De Vos, Maarten | Univ. of Oxford |
Co-Chair: Kidmose, Preben | Aarhus Univ. Denmark |
Organizer: De Vos, Maarten | Univ. of Oxford |
Organizer: Kidmose, Preben | Aarhus Univ. Denmark |
Organizer: Casson, Alexander James | The Univ. of Manchester |
Organizer: Hairston, W. David | Us Army Res. Lab |
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10:00-10:15, Paper ThBT8.1 | |
Real-Life Ear-EEG (I) |
Kappel, Simon Lind | Aarhus Univ. Denmark |
Kidmose, Preben | Aarhus Univ. Denmark |
Keywords: Neural interfaces - Bioelectric sensors
Abstract: Among functional brain scanning methods, electroencephalography (EEG) is the most promising method for non-invasive brain monitoring in real-life environments. Ear-EEG is a method where signals are recorded from electrodes placed on an earpiece inserted into the ear. The compact and discreet nature of ear-EEG devices makes it suitable for long-term real-life recordings. In this study, EEG were recorded from 6 subjects with conventional scalp EEG and dry-contact ear-EEG. All recordings were performed with the same instrumentation and paradigms in both a lab setting and a real-life setting. The study comprised four paradigms: auditory steady-state response (ASSR), steady-state visual evoked potential (SSVEP), auditory onset response, and alpha band modulation. For both settings, the investigated responses were observable and statistically significant (p<0.05) in recordings from ear-electrodes referenced to a scalp electrode (Cz). Statistically significant ASSR and SSVEP were measured in the lab setting by ear-electrodes referenced to an electrode within the same ear. In the real-life setting, only the ASSR was statistically significant for a reference within the same ear. The results demonstrates that ear-EEG recordings can be performed with dry-contact electrodes in real-life.
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10:15-10:30, Paper ThBT8.2 | |
The Ceegrid: Transparent Electroencephalography (EEG ) Acquisition (I) |
Bleichner, Martin G. | Univ. of Oldenburg |
Debener, Stefan | Univ. of Oldenburg |
Keywords: Brain functional imaging - EEG, Human performance - Activities of daily living, Human performance - Attention and vigilance
Abstract: Ear-centered EEG has the potential to open up new applications for research, diagnostic and therapy. The combination of ear-electrodes, miniaturized EEG amplification and mobile signal acquisition allows brain monitoring beyond the lab in real life situations. However, ear-EEG solutions come at the cost of a limited coverage of the head. There is trade-off between the minimal disturbance of the user and the sensitivity to the signals of interest. Placing electrodes around as well as in the ear canal provides the optimal solution.
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10:30-10:45, Paper ThBT8.3 | |
The Effect of Miniaturization and Galvanic Separation of EEG Sensor Nodes in an Auditory Attention Detection Task (I) |
Mundanad Narayanan, Abhijith | KU Leuven |
Bertrand, Alexander | KU Leuven, Univ. of Leuven |
Keywords: Brain-computer/machine interface, Sensory neuroprostheses - Auditory, Neural signal processing
Abstract: Recent technological advances in the design of concealable miniature electroencephalography (mini-EEG) devices are paving the way towards 24/7 neuromonitoring applications in daily life. However, such mini-EEG devices only cover a small area and record EEG over much shorter inter-electrode distances than in traditional EEG headsets. These drawbacks can potentially be mitigated by deploying a multitude of such mini-EEG devices. In this study, we investigate the effect of using such multi-node EEG recordings with short inter-electrode distances and galvanic separation between the nodes for a use-case in auditory attention detection (AAD). We demonstrate that the AAD performance using galvanically separated short-distance EEG measurements is comparable to using long-distance EEG measurements if in both cases the electrodes are optimally placed on the scalp using a group-LASSO optimization.
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10:45-11:00, Paper ThBT8.4 | |
EEG and EMG Electronic-Tattoo for Neurological Evaluation (I) |
Shustak, Shiran | Tel Aviv Univ |
Steinberg, Stanislav | Tel Aviv Univ |
Inzelberg, Lilah | Tel Aviv Univ |
Hillel, Inbar | Tel Aviv Sourasky Medical Center |
Rand, David | Tel Aviv Univ |
David Pur, Moshe | Tel Aviv Univ |
Fahoum, Firas | Tel Aviv Sourasky Medical Center |
Mirelman, Anat | Tel Aviv Sourasky Medical Center |
Hanein, Yael | Tel Aviv Univ |
Keywords: Neurological disorders - Diagnostic and evaluation techniques, Brain-computer/machine interface, Brain functional imaging - EEG
Abstract: Flexible electrodes offer exciting opportunities in the realm of wearable electrophysiology. In particular, tattoo electrodes are markedly soft and conform neatly to the wearer skin allowing nearly artifact-free facial sEMG recordings. As such, tattoo electrodes offer a unique opportunity to combine EEG and facial EMG capabilities to capture neural and motor functions. Here we report the design, implementation and testing of wireless tattoo-based electrodes for REM sleep behavior disorder (RBD) identification. EMG, EOG and EEG were successfully recorded on a smart phone demonstrating the potential use in the home environment.
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11:00-11:15, Paper ThBT8.5 | |
A Correlation-Based Learning Approach to Determining Listening Attention from Eeg Signals (I) |
Alickovic, Emina | Linkoping Univ |
Gustafsson, Fredrik | Department of Electrical Engineering, Linkoping Univ |
Lunner, Thomas | Eriksholm Res. Centre - Part of Oticon |
Keywords: Neural signals - Information theory
Abstract: In this paper, we study canonical correlation analysis (CCA), which is an attractive way to investigate the correlations between multidimensional datasets, to address the cocktail party problem. Our main contribution is a new approach that utilizes CCA for the classification of the attended sound in acoustically highly complex, cocktail-party settings. Extensive test results show that single-trial attention classification accuracy rates, based on 60 second long batches of data from full-scalp EEG, are satisfactorily high ( 95%), and remain equally high for the subset of only 24 electrodes close to the temporal lobe. These results suggest that CCA is a promising tool in the auditory attention classification in different cocktail-party scenarios, compared with other related approaches. These findings suggest the full utility of CCA in the development of intelligible attention-steered brain-computer interfaces (BCIs) and hearing aids (HAs).
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11:15-11:30, Paper ThBT8.6 | |
Automated Analysis of Ear-EEG for Personalized Sleep Monitoring (I) |
Mikkelsen, Kaare | Univ. of Aarhus |
Sterr, Annette | Univ. of Surrey |
Debener, Stefan | Univ. of Oldenburg |
Dijk, Derk-Jan | U Surrey |
De Vos, Maarten | Univ. of Oxford |
Keywords: Human performance - Sleep, Neural signals - Blind source separation (PCA, ICA, etc.), Brain functional imaging - EEG
Abstract: Polysomnography (PSG) with head-mounted EEG electrodes represents the gold standard in sleep research, but can be cumbersome to mount and is not ideal to sleep with. Here we report the exploration of a new type of superthin electrode, the cEEGrid, for discrete and user-friendly ear-EEG recordings for sleep–wake assessment. Expected modulations of alpha and delta power across the night were confirmed in the data recorded with the new cEEGrid electrode. We also computed correlations between sleep parameters, on the one hand derived from manually annotated PSG data and on the other hand from fully automated cEEGrid data analysis. Obtained correlation values were large and support the idea that the cEEGrid concept is a viable tool for sleep research.
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ThBT9 |
Meeting Room 318B |
Invited Session: Invited Session: New Trends in Perinatal and Pediatric
Imaging (hk924) |
Invited Session |
Chair: Lepore, Natasha | USC / Children's Hospital Los Angeles |
Co-Chair: Linguraru, Marius George | Children's National Health System |
Organizer: Lepore, Natasha | USC / Children's Hospital Los Angeles |
Organizer: Linguraru, Marius George | Children's National Health System |
Organizer: Wang, Yalin | Arizona State Univ |
Organizer: Grisan, Enrico | Univ. of Padova |
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10:00-10:15, Paper ThBT9.1 | |
Pediatric Craniofacial Image Analysis: A Software Perspective (I) |
Paniagua, Beatriz | Kitware, Inc |
Linguraru, Marius George | Children's National Health System |
Cevidanes, Lucia | Univ. of Michigan, School of Dentistry, Department of Ortho |
McCormick, Matt | Kitware, Inc |
Fillion-Robin, Jean-Christophe | Kitware, Inc |
Fishbaugh, James | NYU Tandon School of Engineering |
Gerig, Guido | NYU Tandon School of Engineering |
Enquobahrie, Andinet | Kitware Inc |
Keywords: Fetal and Pediatric Imaging, CT imaging applications, Image feature extraction
Abstract: Imaging-based diagnosis and treatment planning in pediatric craniofacial diseases must incorporate growth knowledge. Here, we will review our past efforts to design and disseminate methods that account for the dynamic growth happening in the different skull structures (i.e. bone, brain) during childhood. We believe this is crucial to accelerate the pace of reproducible research in pediatric craniofacial analysis.
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10:15-10:30, Paper ThBT9.2 | |
Fetal Skull Reconstruction Using Deep Convolutional Autoencoders (I) |
Cerrolaza, Juan J. | Imperial Coll. London |
Li, Yuanwei | Imperial Coll. London |
Biffi, Carlo | Imperial Coll. London |
Gomez, Alberto | King's Coll. London |
Matthew, Jacqueline | King's Coll. London |
Sinclair, Matthew | Imperial Coll. London |
Gupta, Chandni | King's Coll. London |
Knight, Caroline | King's Coll. London |
Rueckert, Daniel | Imperial Coll. London |
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10:30-10:45, Paper ThBT9.3 | |
Personalized, Quantitative and Automatic Treatment Planning of Craniosynostosis (I) |
Porras, Antonio R. | Children's National Medical Center |
Tu, Liyun | Children’s National Health System |
Paniagua, Beatriz | Kitware, Inc |
Enquobahrie, Andinet | Kitware Inc |
Keating, Robert | Children's National Health System |
Rogers, Gary | Children's National Health System |
Linguraru, Marius George | Children's National Health System |
Keywords: Fetal and Pediatric Imaging, CT imaging applications
Abstract: Craniosynostosis is a birth defect in which one or more of the cranial sutures fuse prematurely, thus changing the shape and growth pattern of the skull. We have developed an automatic, personalized and quantitative imaging technology for the diagnosis of craniosynostosis, and the surgical planning of cranial vault reconstruction for its treatment. In addition, we introduce a novel framework to evaluate the surgical outcome that does not involve radiation or sedation in children.
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10:45-11:00, Paper ThBT9.4 | |
Cortical Surface-Based Baby Brain Mapping (I) |
Li, Gang | Univ. of North Carolina at Chapel Hill |
Wang, Li | Unc-Chapel Hill |
Lin, Weili | Unc-Chapel Hill |
Shen, Dinggang | UNC-Chapel Hill |
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11:00-11:15, Paper ThBT9.5 | |
Perinatal Imaging, Image Analysis, Machine Learning and Computer-Assisted Surgery (I) |
Gonzalez Ballester, Miguel Angel | ICREA & Univ. Pompeu Fabra |
Keywords: Fetal and Pediatric Imaging, Image analysis and classification - Machine learning / Deep learning approaches
Abstract: This talk will showcase some of the work carried out at the BCN Medtech research unit of Universitat Pompeu Fabra in Barcelona, Spain. In particular, the focus will be on perinatal and fetal applications, including: imaging and image reconstruction in fetal MRI, machine learning approaches for brain image segmentation and classification for the study of perinatal brain development, and a computer-assisted surgery system for fetal surgery.
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11:15-11:30, Paper ThBT9.6 | |
Human-Level Performance on Automatic Head Biometrics in Fetal Ultrasound Using Fully Convolutional Neural Networks (I) |
Sinclair, Matthew | Imperial Coll. London |
Baumgartner, Christian Frederik | ETH Zürich |
Matthew, Jacqueline | King's Coll. London |
Bai, Wenjia | Imperial Coll. London |
Cerrolaza, Juan J. | Imperial Coll. London |
Li, Yuanwei | Imperial Coll. London |
Smith, Sandra | King's Coll. London |
Knight, Caroline | King's Coll. London |
Kainz, Bernhard | Imperial Coll. London |
Hajnal, Joseph V. | King's Coll. London |
King, Andrew Peter | King's Coll. London |
Rueckert, Daniel | Imperial Coll. London |
Keywords: Image reconstruction and enhancement - Machine learning / Deep learning approaches, Fetal and Pediatric Imaging
Abstract: Measurement of head biometrics from fetal ultrasonography images is of key importance in monitoring the healthy development of fetuses. However, the accurate measurement of relevant anatomical structures is subject to large inter-observer variability depending on user expertise and attention fatigue. To address this issue, an automated method utilizing Fully Convolutional Networks (FCN) is proposed to determine measurements of fetal head circumference (HC) and biparietal diameter (BPD). An FCN was trained on approximately 2000 2D ultrasound images of the head with annotations provided by 45 different clinicians during routine screening examinations to perform semantic segmentation of the head. An ellipse is fitted to the resulting segmentation to mimic the annotation typically produced by a clinician. To assess the model's performance, an intra- and inter-observer variability study was performed, where two experts manually annotated 100 test images. Inter-observer variability was slightly higher than the mean expert-to-model variability for HC (2.16mm vs 1.61mm) and BPD (0.59mm vs 0.50mm) measurements, while Dice coefficient was the same (0.980 vs 0.980). Our results demonstrate that the model performs at a level similar to a human expert but reduces user-specific bias by learning from a large dataset annotated by many sonographers. Additionally, measurements are generated in near real-time at 15fps on a GPU, which could speed up clinical workflow for both skilled and trainee sonographers.
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ThBT10 |
Meeting Room 319A |
Invited Session: Sensors and Actuators for 3D Constructs of Living Cells
(ke7r3) |
Invited Session |
Chair: Wiest, Joachim | Cellasys GmbH |
Co-Chair: Schulze, Frank | German Federal Inst. for Risk Assessment |
Organizer: Wiest, Joachim | Cellasys GmbH |
Organizer: Alexander, Frank | Cellasys GmbH |
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10:00-10:15, Paper ThBT10.1 | |
A Microfluidic Bioreactor for a Physiologic Bone-On-A-Chip System (I) |
Schulze, Frank | German Federal Inst. for Risk Assessment |
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10:15-10:30, Paper ThBT10.2 | |
Magnetic versus Electromagnetic-Fields and the Specific Low Frequent Application in Biophysics (I) |
Koch, Martin | Feldkraft Ltd |
Wiest, Joachim | Cellasys GmbH |
Keywords: Electromagnetic field effects and cell membrane
Abstract: The two terms magnetic and electromagnetic had been defined by J.C.Maxwell in 1855. The first is a DC or low frequent-the second a high frequent field application. In the high frequent application, material constants cannot be neglected and herewith a certain heat generation, which is intended in biomed applications, e.g. Hyperthermia. Here however we avoid to heat up the treated cells and work magnetically (low frequently) with tagged magnetic particles like SPIONs.
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10:30-10:45, Paper ThBT10.3 | |
From Operating Heavy Duty Electric Machines to Application of Magnetic Particles Inside Living Cells/cell-Spheres (I) |
Koch, Martin | Feldkraft Ltd |
Wiest, Joachim | Cellasys GmbH |
Keywords: Electromagnetic field effects and cell membrane
Abstract: Heavy Duty industrial machines are operated with large electric fields safely controlled by a suitable insulation, e.g. a long bushing. Living cells are efficient organic heavy duty systems with a membrane capable to insulate gigantic electric fields higher as such devices, mentioned above. That brought up the idea to apply dynamic (superposed, locally displaced) heavy duty field techniques into the environment of living cells. In one case we move magnetic particles individually (each one of the bulk separately field powered) above the surface of the cell membrane, in order to insert them endocytotically. This application is cold meaning negligible, nearly non-detectible, heat is produced inside the particles.
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10:45-11:00, Paper ThBT10.4 | |
Systems Engineering for Microphysiometry (I) |
Wiest, Joachim | Cellasys GmbH |
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ThBT11 |
Meeting Room 319B |
Invited Session: Signals and Systems for Hearing Study and Hearing Aids
(m486w) |
Invited Session |
Chair: Panahi, Issa | Univ. of Texas at Dallas |
Co-Chair: Hansen, John H.L. | Univ. of Texas at Dallas |
Organizer: Panahi, Issa | Univ. of Texas at Dallas |
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10:00-10:15, Paper ThBT11.1 | |
Why Noise Reduction Is so Critical for the Impaired Auditory System (I) |
Yoho, Sarah | Utah State Univ |
Healy, Eric | The Ohio State Univ |
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10:15-10:30, Paper ThBT11.2 | |
Mobile Research Platform for Hearing Research (I) |
Hansen, John H.L. | Univ. of Texas at Dallas |
Ali, Hussnain | Univ. of Texas at Dallas |
Saba, Juliana | Univ. of Texas at Dallas; CRSS - Cochlear Implant Processin |
Keywords: Physiological systems modeling - Multivariate signal processing, Time-frequency and time-scale analysis - Nonstationary processing, Data mining and processing in biosignals
Abstract: The societal need for assistive hearing devices for users with hearing loss has increased exponentially over the past two decades; however, actual human speech recognition performance with such devices has only seen modest gains relative to the pace of actual digital signal processing (DSP) technology. A major challenge with clinical hearing technologies is the limited ability to run complex signal processing algorithms which would require powerful DSPs at the source. The CCi-MOBILE platform, developed by our center at UT-Dallas, provides the research community with an open-source, software-flexible, and powerful computing research interface to conduct listening studies with either/both hearing-aids and cochlear implants. The platform uses commercially available smartphone/tablet devices as portable sound processors, and is able to provide bilateral electric and acoustic stimulation.
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10:30-10:45, Paper ThBT11.3 | |
Speech Signal Processing for Hearing Aids Using Smartphone (I) |
Panahi, Issa | Univ. of Texas at Dallas |
Thibodeau, Linda | Univ. of Texas at Dallas |
Kehtarnavaz, Nasser | Univ. of Texas at Dallas |
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10:45-11:00, Paper ThBT11.4 | |
Multimodal Signal Processing and Machine Learning for Hearing Devices with Both Audio and Non-Audio Sensors: A New Frontier (I) |
Zhang, Tao | Starkey Hearing Tech |
Keywords: Time-frequency and time-scale analysis - Time-frequency analysis, Adaptive filtering, Neural networks and support vector machines in biosignal processing and classification
Abstract: With advances in wireless technology and sensor miniaturization, more non-audio sensors are integrated into ear-level hearing devices. These sensors help improve speech understanding and sound quality and enhance usability. However, the introduction of these sensors also present a new set of challenges to researchers and engineers. Compared with traditional audio sensors, these new sensor inputs come from different modalities and often have different scales and different sampling frequencies. In some cases, they are not even linear and not synchronized to each other at all. In this paper, we will review these challenges in details in the context of hearing devices. Furthermore, we will demonstrate how multimodal signal processing and machine learning can be used to overcome these challenges and bring greater degree of satisfactions to the end users. Finally, how to choose an appropriate approach in different situations will be discussed
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ThBT12 |
Meeting Room 321A |
Invited Session: Progress in Fetal Monitoring Technologies (rm5q6) |
Invited Session |
Chair: Khandoker, Ahsan H | Khalifa Univ. of Science, Tech. and Res |
Co-Chair: Alangari, Haitham M. | Khalifa Univ |
Organizer: Khandoker, Ahsan H | Khalifa Univ. of Science, Tech. and Res |
Organizer: Kimura, Yoshitaka | Tohoku Univ |
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10:00-10:15, Paper ThBT12.1 | |
Fetal Congenital Heart Defects Change the Fetal-Maternal Heart Rate Coupling Strength (I) |
Alangari, Haitham M. | Khalifa Univ |
Khandoker, Ahsan H | Khalifa Univ. of Science, Tech. and Res |
Keywords: Cardiovascular assessment and diagnostic technologies
Abstract: Monitoring fetal heart rate in an important aspect in evaluating fetal well being. Maternal fetal interaction has shown evolution during fetal maturation. In this work, we studied maternal-fetal heart rate synchronization in early and late gestation fetuses. We also evaluated variations in the synchronization due to congenital heart defect (CHD).
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10:15-10:30, Paper ThBT12.2 | |
Time-Variant Maternal-Fetal Cardiac Coupling (I) |
Schulz, Steffen | Univ. of Applied Sciences Jena |
Khandoker, Ahsan | Khalifa Univ |
Voss, Andreas | Univ. of Applied Sciences Jena |
Keywords: Cardiovascular assessment and diagnostic technologies, Diagnostic devices - Physiological monitoring
Abstract: Several different studies demostrated that an certain influence of maternal heart rate on fetal heart rate at short and larger time scales exist while other failed to identify such relationships. Therefore, the aim of this study was to investigate if maternal-fetal cardiac couplings in 22 mid gestation healthy fetuses are changing over time. To quantify the time-variant short-term maternal–fetal cardiac couplings we applied the normalized short time partial directed coherence approach on maternal and fetal ecg recordings. Short-term maternal-fetal cardiac couplings (strength and direction) are changing over time. While the causal influence of maternal (driver) on fetal heart rate was stronger at time lags of τ=1-20 beats this behavoiur changed significantly after a lag τ>20 beats. This finding pointing to an altering maternal-fetal cardiac coupling process over time.
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ThBT13 |
Meeting Room 321B |
MR Neuroimaging (Theme 2) |
Oral Session |
Chair: Parhi, Keshab | Univ. of Minnesota |
Co-Chair: Ma, Heather Ting | Harbin Inst. of Tech. Shenzhen Graduate School |
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10:00-10:15, Paper ThBT13.1 | |
The Correlation Analysis between DTI Network Parameters and AVLT Scale Scores of Alzheimer's Disease |
Guo, Xin | Harbin Inst. of Tech. Shenzhen Graduate School |
Gao, Na | Harbin Inst. of Tech |
Wang, Yan | Harbin Inst. of Tech. Shenzhen Graduate School |
Yang, Yanwu | Harbin Inst. of Tech. Shenzhen Graduate School |
Ma, Heather Ting | Harbin Inst. of Tech. Shenzhen Graduate School |
Keywords: Magnetic resonance imaging - Diffusion tensor, diffusion weighted and diffusion spectrum imaging, Brain imaging and image analysis, Image segmentation
Abstract: Neuroimaging and neuropsychology are employed to investigate the pathological features and clinical characteristics of Alzheimer’s disease (AD) in order to find a method for the precise treatment. Diffusion tensor imaging (DTI) provides a non-intrusive examination of cranial nerve diseases which can help us observe the microstructure of neuron fibers. Building the brain network provides a chance to reveal the significance of specific brain region and the relevance among different regions. In this study, we propose a completely novel method to analyze AD. First whole brain network is built on the basis of a novel segmentation atlas, and global graph theoretical parameters are calculated to evaluate the characteristic of whole brain. Then graph theoretical parameters of specific brain regions are extracted based on whole brain network. Finally neuropsychology scale are employed and we analyze the correlation between graph theoretical parameters of specific regions and scale scores. Our results illustrate the connection between neuroimaging data and neuropsychological scores, and provide a reasonable explanation for the potential connection between clinical performance and physiological brain lesions of AD patients.
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10:15-10:30, Paper ThBT13.2 | |
Left Fimbria Atrophy Is Associated with Hippocampal Metabolism in Female Major Depressive Disorder Patients |
Xu, Jiale | Shanghai Jiao Tong Univ. of Biomedical Engineering A |
Tang, Yingying | Shanghai Mental Health Center, Shanghai Jiao TongUniversity Scho |
Baro, Cecilio | Shanghai Jiao Tong Univ. of Biomedical Engineering |
Zhang, Xiaoliu | Shanghai Jiao Tong Univ. School of Biomedical Engineering |
Meng, Ziyu | Shanghai Jiao Tong Univ |
Li, Yao | Shanghai Jiao Tong Univ |
Keywords: Magnetic resonance imaging - MR neuroimaging, Magnetic resonance imaging - MR spectroscopy, Multimodal imaging
Abstract: Despite the high incidence of major depressive disorder (MDD) in females, the detailed neurobiology mechanism remains not fully understood. Increasing evidence showed that MDD was associated with hippocampal volumetric abnormality with different subfields demonstrating various alteration features. However, the linkage between hippocampal atrophy with its biochemical information remains unclear. In this study, we aim to investigate the relationship between bilateral hippocampal subfields volumetric and metabolic information in female MDD patients, using a combined T1-weighted magnetic resonance imaging (MRI) and proton magnetic resonance spectroscopy (1H-MRS) technology. There are 15 female MDD patients and 12 matched healthy controls involved in the study. We found a significant decrease in left fimbria volume in MDD group, which was negatively correlated with left hippocampal choline level. In addition, the left hippocampal creatine concentration in patients was negatively correlated with left fimbria volume. Moreover, the NAA level in left hippocampus was negatively correlated with MDD clinical symptomology including anxiety and depression scores. Our findings suggest that the altered coupling between hippocampal structural and metabolic features might contribute to the etiology of female MDD patients.
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10:30-10:45, Paper ThBT13.3 | |
Multivariate Analysis of White Matter Structural Networks of Alzheimer’s Disease |
Ye, Chenfei | Harbin Inst. of Tech. Shenzhen Graduate School |
Wang, Xiaoni | XuanWu Hospital of Capital Medical Univ |
Han, Ying | XuanWu Hospital of Capital Medical Univ |
Ma, Heather Ting | Harbin Inst. of Tech. Shenzhen Graduate School |
Yang, Yanwu | Harbin Inst. of Tech. Shenzhen Graduate School |
Keywords: Magnetic resonance imaging - MR neuroimaging, Magnetic resonance imaging - Diffusion tensor, diffusion weighted and diffusion spectrum imaging, Multivariate image analysis
Abstract: The connectome-wide association studies exploring the association between brain connectome and disease phenotypes have suffered from a massive number of comparisons. In this paper, we propose to apply a multivariate distance-based analytic framework on brain white matter (WM) structural networks invaded by Alzheimer’s disease (AD). Eighty-three subjects including patients with AD, amnestic mild cognitive impairment (aMCI) and healthy subjects were scanned with dMRI. By constructing WM structural network for each individual, we used both multivariate and traditional univariate statistical models to complimentarily analyze network pattern and fiber strength changes due to AD. WM connections linked with several brain structures were found significantly changed between AD group and normal controls. No significant findings were observed between aMCI group and normal controls. Our results demonstrate the sensitivity of the combined connectome-based analytic framework in detecting abnormalities of structural brain networks.
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10:45-11:00, Paper ThBT13.4 | |
Altered Fractional Amplitude of Low Frequency Fluctuations in Unmedicated Female Patients with Obsessive-Compulsive Disorder |
Meng, Ziyu | Shanghai Jiao Tong Univ |
Zhang, Zongfeng | Shanghai Mental Health Center, Shanghai Jiao Tong Univ. Sch |
Fan, Qing | Shanghai Mental Health Center, Shanghai Jiao Tong Univ. Sch |
Li, Yao | Shanghai Jiao Tong Univ |
Keywords: Magnetic resonance imaging - MR neuroimaging, Functional image analysis, Brain imaging and image analysis
Abstract: A number of resting-state functional magnetic resonance imaging (rs-fMRI) studies indicate dysfunction of large-scale brain networks underlying the pathophysiology of obsessive-compulsive disorder (OCD). Recent epidemiology studies show that the prevalence of female OCD patients is higher than that of males. However, the underlying neurobiology mechanism for female OCD patients remains not fully understood. In this study, we are aimed to explore the spontaneous brain neuronal activity in unmedicated female OCD patients using rs-fMRI methodology and fractional amplitude of low frequency fluctuations (fALFF) analysis. Additionally, we examine the relationship between fALFF changes and female OCD symptomatology. Increased fALFF values in right brainstem, right rectus, left middle temporal gyrus and right angular were found in OCD females. And decreased fALFF values in right cerebellum, left middle occipital gyrus, left insula, postcentral gyrus and left precentral gyrus were shown in female OCD patients. Moreover, the fALFF values in left precentral gyrus and left middle temporal gyrus were positively associated with patients YBOCS-Obsessions scores and HAMD scores, respectively. Our findings bring additional insights in understanding the pathophysiology of female OCD patients.
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11:00-11:15, Paper ThBT13.5 | |
Diagnostic Classification of Autism Using Resting-State Fmri Data and Conditional Random Forest |
A.R., Jac Fredo | San Diego State Univ |
Jahedi, Afrooz | San Diego State Univ |
Reiter, Maya | San Diego State Univ |
Müller, Ralph-Axel | San Diego State Univ |
Keywords: Magnetic resonance imaging - MR neuroimaging
Abstract: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that is associated with atypical connectivity within and between brain regions. In this study, we attempted to classify functional Magnetic Resonance Images (fMRI) of Typically Developing (TD) and ASD participants using conditional random forest and random forest. Resting-state fMRI images of TD and ASD participants (N=320 for training and N=80 for validation) were obtained from the Autism Imaging Data Exchange; ABIDE-I, ABIDE-II. Images were preprocessed using a standard pipeline. A Functional Connectivity (FC) matrix was calculated using 237 cortical, subcortical, and cerebellar Regions of Interest (ROIs). The dimensionality of the FC matrix was reduced using conditional random forests and at each dimension classification accuracy was tested using random forests. Results suggest that in the current dataset, the random forest is able to classify the TD and ASD with a peak accuracy of 65% using 143 features. Remarkably, the Cingulo-Opercular Task Control (COTC) region contributed the highest number of features linked to more accurate classification, and connectivity between COTC and the dorsal attention network distinguished ASD and TD participants.
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11:15-11:30, Paper ThBT13.6 | |
Biomarkers for Adolescent MDD from Anatomical Connectivity and Network Topology Using Diffusion MRI |
Chu, Shu-Hsien | Univ. of Minnesota |
Lenglet, Christophe | Univ. of Minnesota |
Westlund Schreiner, Melinda | Univ. of Minnesota |
Klimes-Dougan, Bonnie | Univ. of Minnesota |
Cullen, Kathryn R. | Univ. of Minnesota |
Parhi, Keshab | Univ. of Minnesota |
Keywords: Magnetic resonance imaging - Diffusion tensor, diffusion weighted and diffusion spectrum imaging, Brain imaging and image analysis, Image feature extraction
Abstract: Due to the high resistance (35%) to the current treatment methods in adolescent Major Depressive Disorder (MDD) and its tragic outcomes, the discovery of treatment-related responders is critical to developing effective treatments. In this paper, the permutation test is performed to identify statistically significant changes in anatomical characteristics during pairwise comparisons among the control group (n=27), treated MDD group (n=37), and untreated MDD group (n=15). The anatomical characteristics include: 1) anatomical connectivity defined using DTI metrics between a pair of brain regions, and 2) topological measurements of anatomical networks. With the Bonferroni correction for multiple-comparison, significant alterations in community structure and local topology were identified as the p-value < 5%, which include: 1) a reduced nodal centrality (degree and strength) on right hippocampus for treated compared to untreated group, 2) an elevated clustering coefficient and local efficiency on right lateral orbitofrontal cortex for untreated compared to the combination of control and treated groups, 3) an increased participation coefficient for untreated patients on left insula cortex in the mean-diffusivity network compared to the combination of control and treated groups, and 4) a degraded module degree z-score on right caudate nucleus for all the patients compared to the control group. Two connections, hippocampus-insula in the right hemisphere and parahippocampal-insula in the left hemisphere, were found significantly altered in TR, AD, and FA due to MDD.
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ThBT14 |
Meeting Room 322AB |
Minisymposia: Non-Contact and Remote Measurement of Blood Pressure and
Perfusion Based on Video Pulse Waves (i19sv) |
Minisymposium |
Chair: Yoshizawa, Makoto | Tohoku Univ |
Co-Chair: Tanaka, Akira | Fukushima Univ |
Organizer: Yoshizawa, Makoto | Tohoku Univ |
Organizer: Tanaka, Akira | Fukushima Univ |
|
10:00-10:15, Paper ThBT14.1 | |
A Basic Study on Noncontact Pulse Transit Time Estimation Using Camera and Microwave Sensor (I) |
Yoshioka, Mototaka | Panasonic Corp |
Bounyong, Souksakhone | Panasonic Corp |
Keywords: Physiological monitoring - Instrumentation, Physiological monitoring - Novel methods
Abstract: In this symposium, noncontact-based vital sign measurements for daily monitoring is discussed. In particular, our system remotely estimates pulse transit time (PTT) using camera and microwave sensor. A microwave sensor detects heartbeats from subject’s chest movement, and a camera sensor obtains pulse wave signals from change of skin’s brightness. By accurately synchronizing these sensors, the system calculates the time difference between a heartbeat and a pulse, thus PTT is estimated. An experiment conducted by twelve subjects resulted in physically measurement PTT (around 180 ms).
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10:15-10:30, Paper ThBT14.2 | |
Extraction of Blood Pressure Information from Video Plethysmography (I) |
Sugita, Norihiro | Tohoku Univ |
Yoshizawa, Makoto | Tohoku Univ |
Tanaka, Akira | Fukushima Univ |
Abe, Makoto | Shinshu Univ |
Homma, Noriyasu | Tohoku Univ. Graduate School of Medicine |
Yambe, Tomoyuki | Tohoku Univ |
Keywords: Optical and photonic sensors and systems, Physiological monitoring - Novel methods, New sensing techniques
Abstract: In a previous study, our group showed the pulse wave transit time obtained from two areas in a video image positively correlated with blood pressure changes. However, this result does not agree with the principle of the pulse wave transit time. In this study, we show not only the reason for this result but also the possibility of estimating blood pressure changes from one area in a video image.
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10:30-10:45, Paper ThBT14.3 | |
Application of Non-Contact Video Plethysmography to Analysis of Local Vascular Regulation (I) |
Tanaka, Akira | Fukushima Univ |
Yamada, Yuya | Graduate School of Symbiotic System Science and Tech. Fuku |
Yoshizawa, Makoto | Tohoku Univ |
Keywords: Physiological monitoring - Instrumentation, Optical and photonic sensors and systems
Abstract: The aim of this study is to propose an extraction method of video plethysmograpy (VPG) from not only face but also the skin with a few capillary vessels. The extraction algorithm is based on periodic component analysis. The results indicated that the proposed method can extract valid pulse wave which has the information of local vascular regulations from a region of interest (ROI) located in a part other than a face.
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ThBT15 |
Meeting Room 323A |
Invited Session: Recent Advances in System, Algorithm and Applications of
Diagnostic Ultrasound Imaging Modality (mrn47) |
Invited Session |
Chair: Managuli, Ravi | Hitachi Aloka Medical America, Inc |
Co-Chair: Kim, Hyung Ham | Pohang Univ. of Science and Tech |
Organizer: Managuli, Ravi | Hitachi Aloka Medical America, Inc |
Organizer: Kim, Hyung Ham | Pohang Univ. of Science and Tech |
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10:00-10:15, Paper ThBT15.1 | |
Single Cell Mechanics Study Using Single-Beam Acoustic Tweezers (I) |
Kim, Hyung Ham | Pohang Univ. of Science and Tech |
lim, Hae Gyun | Pohang Univ. of Science and Tech |
Keywords: Ultrasound imaging - High-frequency technology
Abstract: Evaluation of cell mechanics plays a vital role in predicting and evaluating diseases in medical and clinical fields. Moreover, the mechanical stiffness level indicates the metastasis potential in tumor cells. In this study, the biomechanical properties of breast cancer cells were investigated by single-beam acoustic tweezers (SBAT), a non-destructive assessment tool. We demonstrated that SBAT is a new promising tool for quantifying the mechanical phenotype of cells at the single-cell level without labeling.
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10:15-10:30, Paper ThBT15.2 | |
Recent Advances in Ultrasound Imaging: Breast, Liver and Contrast (I) |
Managuli, Ravi | Hitachi Aloka Medical America, Inc |
Keywords: Ultrasound imaging - Breast, Ultrasound imaging - Elastography, Ultrasound imaging - Interventional
Abstract: Ultrasound is a powerful imaging modality available to clinicians, engineers and researchers today. In recent years, advances in computing, electronics, transducer, contrast imaging and signal/imaging processing algorithms have fueled the growth of US devices in many clinical applications. Three main new technology and applications discussed in this presentation are: tomographic imaging of breast, fibrosis staging of liver, and use of contrast agent for differentiating benign from malignant lesions. Current state-of-the-art technology in each of these applications will be discussed along with the associated clinical advantages. We will also outline limitations and future challenges of each of these technologies.
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10:30-10:45, Paper ThBT15.3 | |
Development of 3D Photoacoustic Imaging System and Its Clinical Translation (I) |
Shiina, Tsuyoshi | Kyoto Univ |
Keywords: Ultrasound imaging - Breast, Ultrasound imaging - Elastography, Ultrasound imaging - Photoacoustic/Optoacoustic/Thermoacoustic
Abstract: PA imaging has been explored for the early diagnosis of diseases by imaging tumor angiogenesis and blood oxygen saturation. We have developed a 3D photoacoustic mammography system for breast cancer diagnosis and demonstrated that 3D imaging of tumor-related vessels can be realized with a resolution of less than 0.5mm using the prototype with hemispherical sensors. In addition, this device was applied to analyze peripheral blood vessels, such as those in the palm. Results indicated that the PA imaging system enabled visualization of the 3D features of blood vessels in the palm and noninvasive analysis of arterial tortuousness.
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10:45-11:00, Paper ThBT15.4 | |
A New Surgical Approach to Treat the Resistant Hypertension (I) |
Park, Sung-Min | POSTECH |
Baik, Jinhwan | POSTECH |
Keywords: Ultrasound imaging - Interventional, Multimodal imaging
Abstract: Resistant hypertension is a refractory heart disease in which blood pressure cannot be controlled using medication. Catheter-based radiofrequency ablation has been identified as a potential method to treat the resistant hypertension by inactivating the sympathetic nerves along the renal artery. However, a recent clinical trial using this method could not show the efficacy. Here, we demonstrate a hypothesis of failure of catheter based method and propose an alternative surgical approach to the treatment of resistant hypertension. We describe a surgical instrument design and validate the feasibility of the method using in vitro and ex vivo studies.
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11:00-11:15, Paper ThBT15.5 | |
Introducing Diagnostic Ultrasound Course in Undergraduate BME Programs (I) |
Krishnan, Shankar | WIT |
Keywords: Ultrasound imaging - Photoacoustic/Optoacoustic/Thermoacoustic, Image enhancement, Ultrasound imaging - High-frequency technology
Abstract: Introducing a medical ultrasound course at the undergraduate level in biomedical engineering programs will be beneficial to students. However, addition of such a course in BME programs encounters several constraints. The objective of this present initiative is to propose an undergraduate elective course on diagnostic ultrasound for BME students. Two models of diagnostic ultrasound course are proposed. The first is designed with lecture-based pedagogy. The second is an innovative model with complimentary lab modules based on clinical collaboration. Preliminary feedback lends support to the feasibility of the proposed models.
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ThBT16 |
Meeting Room 323B |
Invited Session: Biologically Inspired Regenerative Systems (r5h4u) |
Invited Session |
Chair: Jabbari, Esmaiel | Univ. of South Carolina |
Co-Chair: Varghese, Shyni | Univ. of California San Diego |
Organizer: Jabbari, Esmaiel | Univ. of South Carolina |
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10:00-10:15, Paper ThBT16.1 | |
Paper-Based Biomaterials for Personalized Medicine and Regenerative Engineering (I) |
Camci-Unal, Gulden | Univ. of Massachusetts Lowell |
Keywords: Scaffolds in tissue engineering
Abstract: Traditional tissue engineering models use sophisticated instrumentation or costly set-ups for fabrication of 3D scaffolds, require extensive optimization procedures, and do not provide physiologically relevant size structures without mass transport limitations. Therefore, it is challenging to fabricate biocompatible scaffolds for personalized medicine. To tackle these hurdles, we developed paper-based cell culture platforms for a range of applications that involve the use of different types of cells.
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10:15-10:30, Paper ThBT16.2 | |
Functionally Graded Biomaterials for Tissue Regeneration (I) |
Yang, Yunzhi | Stanford Univ |
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10:30-10:45, Paper ThBT16.3 | |
Biomineralized Materials As Bone ECM Mimetics: From Understanding Molecular Mechanisms to New Therapeutic Interventions (I) |
Varghese, Shyni | Univ. of California San Diego |
Keywords: Biomimetic materials, Biomaterial-cell interactions - Functional biomaterials, Biomaterial-cell interactions - Surface modification of biomaterials
Abstract: Reciprocal interactions of cells with their microenvironment are fundamental to multiple cellular processes necessary for tissue development, homeostasis, and regeneration. To this end, biomimetic systems emulating the physical and chemical properties of tissue specific extracellular matrices are being developed at a rapid pace. Mineral environment of the bone tissue plays a key role in maintaining the bone health and tissue homeostasis. In this talk, I will discuss our efforts to delineate the role of the mineralized extracellular matrix on cellular responses relevant to bone tissue repair, stem cell differentiation, and bone degenerative diseases.
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10:45-11:00, Paper ThBT16.4 | |
Zonal Regeneration of Articular Cartilage (I) |
Jabbari, Esmaiel | Univ. of South Carolina |
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ThBT17 |
Meeting Room 323C |
Physiological Modeling and Analysis (Theme 7) |
Oral Session |
Chair: Mortazavi, Bobak | Texas A&M Univ |
Co-Chair: Selvaraj, Nandakumar | Vital Connect Inc |
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10:00-10:15, Paper ThBT17.1 | |
Investigation of Key Variables Impacting ICM Sensing Using Computer Simulations |
Sun, Stephanie | Abbott |
Min, Xiaoyi | St. Jude Medical, Inc |
Healey, Glenn | Univ. of California, Irvine |
Keywords: Implantable sensors, Modeling and analysis, Physiological monitoring - Modeling and analysis
Abstract: An insertable cardiac monitor (ICM) is a small medical device that is placed under the chest muscle to continuously monitor electrical heart activities and record electrocardiograms (ECGs). Clinicians use it to diagnose and manage abnormal heart activities in patients with unexplained syncope, palpitations, cryptogenic stroke, lightheadedness, dizziness, and seizures. However, clinical studies showed that false detection rates of abnormal heart rhythms are still high, and key variables can cause the ICM to detect heart signals inappropriately by altering amplitudes and morphologies of ECGs. The objective of this paper is to investigate the effects of these key variables on ICM sensing by using computer simulations and virtual human family. This study uses Sim4Life finite element analysis (FEA) software to simulate cardiac propagation and ICM electrode sensing inside three members of a virtual human family. The ICM CAD model was used and placed in each member at various locations and with electrodes facing up or down. The propagation vectors in the hearts are approximated by fields created along the heart axis going in the direction from the left atrium (LA) and right atrium (RA) disc pair to apex disc. After solving the models, the voltage difference on the electrodes is obtained from each simulation with a model placement. In the adult male model, the results at default 45 degree was scaled to the clinical data with the similar BMI range, and the scaling factor was applied to all the simulation results. We observed in these simulations that sensing amplitudes can vary greatly depending on device flipping, orientation/rotation, and migration; change significantly due to respiration effect; and are most sensitive to body mass with the similar trend from clinical data. Those findings support identification of the key variables impacting clinical false detections.
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10:15-10:30, Paper ThBT17.2 | |
Monitoring Lung Mechanics During Mechanical Ventilation Using Machine Learning Algorithms |
Hezarjaribi, Niloofar | Washington State Univ |
Dutta, Rabijit | Univ. of Idaho |
Tao, Xing | Univ. of Idaho |
Gordon, Murdoch | Univ. of Idaho |
Mazrouee, Sepideh | Univ. of California San Diego |
Mortazavi, Bobak | Texas A&M Univ |
Ghasemzadeh, Hassan | Washington State Univ |
Keywords: Modeling and analysis, Integrated sensor systems, Mechanical sensors and systems
Abstract: Evaluation of lung mechanics is the primary component for designing lung protective optimal ventilation strategies. This paper presents a machine learning approach for bedside assessment of respiratory resistance (R) and compliance (C). We develop machine learning algorithms to track flow rate and airway pressure and estimate R and C continuously and in real-time. An experimental study is conducted, by connecting a pressure control ventilator to a test lung that simulates various R and C values, to gather sensor data for validation of the devised algorithms. We develop supervised learning algorithms based on the decision tree, decision table, and Support Vector Machine (SVM) techniques to predict R and C values. Our experimental results demonstrate that the proposed algorithms achieve 90.3%, 93.1%, and 63.9% accuracy in assessing respiratory R and C using decision table, decision tree, and SVM, respectively. These results along with our ability to estimate R and C with 99.4% accuracy using a linear regression model demonstrate the potential of the proposed approach for constructing a new generation of ventilation technologies that leverage novel computational models to control their underlying parameters for personalized healthcare and context-aware interventions.
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10:30-10:45, Paper ThBT17.3 | |
Synthetic Sensor Data Generation for Health Applications: A Supervised Deep Learning Approach |
Norgaard, Skyler | Kalamazoo Coll |
Saeedi, Ramyar | Washington State Univ |
Sasani, Keyvan | Washington State Univ |
Gebremedhin, Assefaw | Washington State Univ |
Keywords: Wearable sensor systems - User centered design and applications, Sensor systems and Instrumentation, Modeling and analysis
Abstract: Recent advancements in mobile devices, data analysis, and wearable sensors render the capability of in-place health monitoring. Supervised machine learning algorithms, the core intelligence of these systems, learn from labeled training data. However, labeling vast amount of data is time-consuming and expensive. Moreover, sensor data can often contain personal information that a user may not be comfortable sharing. Therefore, there is a strong need to develop methods for generating realistic labeled sensor data. In this paper, we propose a supervised generative adversarial network architecture that learns from feedback from both a discriminator and a classifier in order to create synthetic sensor data. We demonstrate the effectiveness of the architecture on a publicly available human activity dataset. We show that our generator learns to output diverse samples that are similar but not identical to the training data.
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10:45-11:00, Paper ThBT17.4 | |
Comparisons of Oscillometric Blood Pressure Measurements at Different Sites of the Upper Limb |
Liu, Jing | The Chinese Univ. of Hong Kong |
Ou, Yanghui | Hong Kong Univ. of Science and Tech |
Yan, Bryan P. | Prince of Wales Hospital, the Chinese Univ. of Hong Kong |
Sodini, Charles | Massachusetts Inst. of Tech |
Zhao, Ni | The Chinese Univ. of Hong Kong |
Keywords: Physiological monitoring - Instrumentation
Abstract: The importance of home blood pressure (BP) monitoring has been emphasized for effective hypertension management. Currently, the most popular non-invasive BP monitors for home use are the upper arm cuff-style oscillometric devices which determine BP from the cuff pressure oscillations during the cuff inflation/deflation induced by the pulsatile blood flow in the compressed arteries. However, the large size of the upper arm cuff is not favorable for attachment in daily life for ambulatory BP monitoring. Therefore, the miniaturization of home BP monitors is in demand to improve their portability for frequent measurements. This work examined the oscillometric measurement of mean blood pressure(MBP) at upper arm (UA), middle forearm (MA), wrist (WR), finger proximal phalanx (FP) and finger distal phalanx (FD) on 14 young adults. The experimental results showed that the mean and standard deviation of the differences from the oscillometric MBP at UA are 8.86±6.28 mm Hg at MA, 14.43±5.52 mm Hg at WR, 9.80±6.57 mm Hg at FP and -0.77±6.37 mm Hg at FD, respectively. Based on hand checking and literature data, the order of the ratios of the bone volume to the surrounding tissue volume from large to small is WR>MA≈FP>FD≈UA. Together with the experimental results, we infer that a larger bone-tissue ratio could result in a larger oscillometric MBP reading. Since the applied cuff pressure are supposed to be less effectively absorbed by the soft-tissue surrounding a larger rigid bone, it is more difficult to occlude the arteries buried in the pressure-absorbing tissue at a bonier site by the inflatable cuffs, which leads to a higher measured MBP than the real MBP. In conclusion, it is promising to develop finger oscillometric BP monitors worn on the finger distal phalanx which have a compact size and provide consistent measurement results with the UA measurements.
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11:00-11:15, Paper ThBT17.5 | |
Vomit Comet Physiology: Autonomic Changes in Novice Flyers |
Johnson, Kristina | Massachusetts Inst. of Tech |
Taylor, Sara | Massachusetts Inst. of Tech |
Fedor, Szymon | Massachusetts Inst. of Tech |
Jaques, Natasha | Massachusetts Inst. of Tech |
Chen, Weixuan | Massachusetts Inst. of Tech |
Picard, Rosalind | Massachusetts Inst. of Tech |
Keywords: Physiological monitoring - Novel methods, Wearable sensor systems - User centered design and applications, Physiological monitoring - Modeling and analysis
Abstract: This exploratory study examined the effects of varying g-forces, including feelings of weightlessness, on an individual’s physiology during parabolic flight. Specifically, we collected heart rate, accelerometer, and skin conductance measurements from 16 flyers aboard a parabolic flight using wearable, wireless sensors. The biosignals were then correlated to participant reports of nausea, anxiety, and excitement during periods of altered g-forces. Using linear mixed-effects models, we found that (1) heart rate was positively correlated to individuals' self-reported highest/lowest periods of both anxiety and excitement, and (2) bilateral skin conductance asymmetry was positively correlated to individuals' self-reported highest/lowest periods of nausea.
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11:15-11:30, Paper ThBT17.6 | |
A Novel Synthetic Simulation Platform for Validation of Breathing Rate Measurement |
Selvaraj, Nandakumar | Vital Connect Inc |
Nallathambi, Gabriel | VitalConnect |
Kettle, Paul | PKettle Consulting |
Keywords: Wearable low power, wireless sensing methods, Physiological monitoring - Modeling and analysis, Bio-electric sensors - Sensor systems
Abstract: Validation of biosensor algorithms is paramount for regulated medical devices applied to patient monitoring. We present validation of breathing rate (BR) measurement using a patch medical device via a novel synthetic simulation platform, in-hospital data collection and controlled laboratory study. Single-lead ECG and triaxial body acceleration signals with variability and noise are synthetically generated and quantized for a constellation according to the input parameters of heart rate (HR) as a fundamental frequency(fc) of ECG and reference BR as a modulating frequency (fr). Synthetic signals are input to the BR algorithms and the performance of output BRs are evaluated for a region-of-interest of the constellation (fc/fr ≥ 3 & fc/fr ≤ 8) accounting the Nyquist and physiological varability. The performances of patch sensor’s BR are also evaluated in 13 post-operative patients with reference to a clinical bedside monitor and in 57 subjects carrying out a controlled laboratory protocol with reference to capnography. The synthetic simulations revealed mean absolute error (MAE) of 0.8±0.6 brpm and standard deviation of absolute error of 0.3±0.2 brpm for the BR algorithms of patch sensor. The controlled laboratory testing revealed MAE of 1.7±0.7 brpm (n=57) for stationary conditions. The proposed simulation platform can be useful for developmental refinement or validation of BR measurement prior to testing in humans at clinical or laboratory conditions and applicable for testing other patient monitoring devices with modular modifications.
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ThBT18 |
Meeting Room 324 |
Wearable Systems (Theme 7) |
Oral Session |
Chair: Samadani, Ali | Philips Res. North America |
Co-Chair: Casson, Alexander James | The Univ. of Manchester |
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10:00-10:15, Paper ThBT18.1 | |
Efficient Design of Real Time Bio-Signal Preprocessing for Wearable Devices |
Yoon, Seung Keun | Samsung Advanced Inst. of Tech |
Lee, Jongwook | Samsung Electronics |
Kwon, Uikun | Samsung Electronics |
Ko, Byung-Hoon | Samsung Advanced Inst. of Tech |
Kim, Youn Ho | Samsung Advanced Inst. of Tech |
Keywords: Wearable low power, wireless sensing methods, Bio-electric sensors - Sensor systems, Optical and photonic sensors and systems
Abstract: Wearable devices for body-status monitoring require various signal processing such as ambient noise filtering and signal quality evaluation. While wearable devices are very limited in resource, conventional noise filtering and signal quality evaluating methods consume considerable amount of processing power. Moreover, these conventional methods are not suitable for processing bio-signals in terms of its performance. In this paper, we propose a novel method of preprocessing bio-signals. This preprocessing method includes distortionless noise filtering and signal quality estimation, where both parts are basically based on a simple combination of multiple low pass IIR filters.
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10:15-10:30, Paper ThBT18.2 | |
Optimizing Energy Harvesting for Foot Based Wearable Sensors |
Beach, Christopher | Univ. of Manchester |
Green, Peter R | Univ. of Manchester |
Casson, Alexander James | The Univ. of Manchester |
Keywords: Wearable power and on-body energy harvesting, Wearable low power, wireless sensing methods, Wearable sensor systems - User centered design and applications
Abstract: Wearable devices have the potential to improve healthcare, but suffer from significant barriers to adoption, including the need for constant recharging. Harvesting energy from the ambient environment to top-up batteries can overcome this, but the actual energy available is very small, and hence it is critical that the whole system is highly optimized. This paper presents an investigation into the optimization of inertial energy harvesters for placement at the human foot. Lower body locations have previously been shown to be very energy dense, however previous energy harvester modeling has focused on the lower leg rather than the foot itself for ease of device placement. We show that the typical energy density can be almost double at the foot compared with lower leg positions, with substantially more energy concentrated in a smaller bandwidth. There is thus a dual benefit of placing a harvester at the foot: there is more energy due to the larger movement of the foot, and more efficient (higher Q) harvesters can be used to increase the collected energy. We place these results in context by analyzing the power demands of a typical wearable and identify that with appropriate harvester tuning the peak current requirements of the electronics can be fitted into the energy peaks generated from each footstep.
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10:30-10:45, Paper ThBT18.3 | |
A Spinal Motion Measurement Protocol Utilizing Inertial Sensors without Magnetometers |
Samadani, Ali | Philips Res. North America |
Lee, Alex | Motion Signature Analysis |
Kulic, Dana | Univ. of Waterloo |
Keywords: Sensor systems and Instrumentation, Novel methods, Modeling and analysis
Abstract: This study presents an approach for instrumenting a spinal motion measurement protocol using two inertial measurement units (IMU)s affixed at the posterior pelvis and superior trunk. The accuracy of the inertial motion measurement instrumentation in tracking the relative orientation of the trunk with respect to the pelvis in three spinal motions (flexion-extension, side bending, and rotation) is compared to that of a concurrent optical motion capture (mocap) system. Six healthy adults (31.5±11.2; 2 females) were recruited to perform the spinal motions. The results show minimal deviations of the IMU measurements from those of the mocap system (RMSE<2deg, r>0.84 in all cases) and demonstrate the efficacy of the proposed instrumentation approach for spinal motion measurement.
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10:45-11:00, Paper ThBT18.4 | |
Personalized Human Activity Recognition Using Wearables: A Manifold Learning-Based Knowledge Transfer |
Saeedi, Ramyar | Washington State Univ |
Sasani, Keyvan | Washington State Univ |
Norgaard, Skyler | Kalamazoo Coll |
Gebremedhin, Assefaw | Washington State Univ |
Keywords: Wearable sensor systems - User centered design and applications, Wearable wireless sensors, motes and systems, Modeling and analysis
Abstract: Human activity recognition (HAR) is an important component in health-care systems. For example, it can enable context-aware applications such as elderly care and patient monitoring. Relying on a set of training data, supervised machine learning algorithms form the core intelligence of most existing HAR systems. Meanwhile, the accuracy of an HAR model highly depends on the similarity between the training and the operating context. Therefore, there is a need for developing machine learning algorithms that can easily adapt to the operating context at hand. In this paper, we propose a cross-subject transfer learning algorithm that links source and target subjects by constructing manifolds from feature-level representation of the source subject(s). Our algorithm assigns labels to the unlabeled data in the current context using the manifold learned from the source subject(s). The newly labeled data is used to develop a personalized HAR model for the current context (i.e. target subject). We demonstrate the efficacy of the algorithm using a publicly available dataset on HAR. We show that the proposed framework improves the accuracy of activity recognition by up to 24%.
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11:00-11:15, Paper ThBT18.5 | |
Tracking Kinematic and Kinetic Measures of Sit to Stand Using an Instrumented Spine Orthosis |
Matthew, Robert Peter | UC Berkeley |
Seko, Sarah | UC Berkeley |
Bailey, Jeannie | Univ. of California at San Francisco |
Bajcsy, Ruzena | UC Berkeley, CITRIS |
Lotz, Jeffrey | Orthopaedic Surgery, Univ. of California at Berkeley |
Keywords: Wearable body sensor networks and telemetric systems, Wearable low power, wireless sensing methods, Wearable sensor systems - User centered design and applications
Abstract: Age related spinal deformity is an becoming increasingly prevalent problem, resulting in decreased quality of life. While spinal deformity can be corrected via surgical intervention, a large number of people with spinal fusions require follow-up surgery due to further degeneration. The identification of changes to a subject's kinematics and kinetics post-surgery are limited by a lack of methods to collect patient-specific motion data over the course of surgical recovery. This paper introduces an Instrumented Spine Orthosis (ISO) that can capture the motions of the subject torso without requiring the use of a control computer or other dedicated motion capture equipment. This system is used to collect the peak torso angles and velocities for a single subject performing sit-to-stand actions. The accuracy of the ISO is evaluated using motion capture, during different sit-to-stand protocols designed to highlight motion changes that have been seen in subjects with reduced mobility. This system was found to provide reliable measurements of these kinematic and kinetic torso measures across all tested motions, demonstrating the potential for the use of Instrumented Spine Orthotics to provide quantitative measures during the surgical recovery process.
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11:15-11:30, Paper ThBT18.6 | |
A Machine Learning Approach to Targeted Balance Rehabilitation in People with Parkinson’s Disease Using a Sparse Sensor Set |
Pickle, Nathaniel | The Univ. of Texas at Dallas |
Shearin, Staci | The Univ. of Texas Southwestern Medical Center |
Fey, Nicholas | The Univ. of Texas at Dallas |
Keywords: Wearable sensor systems - User centered design and applications
Abstract: Clinical balance assessments often rely on functional tasks as a proxy for balance (e.g., Timed Up and Go). In contrast, analyses of balance in research settings incorporate quantitative biomechanical measurements (e.g., whole-body angular momentum, H) using motion capture techniques. Fully instrumenting patients in the clinic is not feasible, and thus it is desirable to estimate biomechanical quantities related to balance from measurements taken from a subset of the body segments. Machine learning algorithms are well-suited for this type of low- to high-dimensional mapping. Thus, our objective was to develop and validate an artificial neural network for estimating contributions to H from 12 body segments using only five inertial measurement units. The network was trained, tested and validated on data from five able-bodied individuals performing forty trials each of a circuit involving complex walking tasks, including stairs, ramp, and direction changes. The network was also separately tested on four trials of an individual with Parkinson’s disease walking on the circuit. The output of the network was strongly correlated with the segment contributions to H in both able-bodied (R=0.997) and Parkinson’s disease (R=0.998) subjects. The estimated values also had low error relative to the signal magnitude, with the largest mean±SD root-mean-squared errors of 8.04±1.76% peak signal magnitude in able-bodied individuals and 7.96±0.91% in the individual with Parkinson’s disease. These promising results establish the feasibility of using a sparse set of inertial measurement units to provide quantitative data to clinicians for targeted balance rehabilitation across different patients.
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ThBT19 |
Meeting Room 325A |
Minisymposia: Emerging Methods in Medical Image Analysis II (1agah) |
Minisymposium |
Chair: Lee, Gobert | Flinders Univ |
Co-Chair: Fujita, Hiroshi | Gifu Univ |
Organizer: Fujita, Hiroshi | Gifu Univ |
Organizer: Lee, Gobert | Flinders Univ |
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10:00-10:15, Paper ThBT19.1 | |
Deep Convolutional Neural Network for Medical Image Analysis - a Few Issues (I) |
Lee, Gobert | Flinders Univ |
Keywords: Image analysis and classification - Machine learning / Deep learning approaches, Image analysis and classification - Digital Pathology, Image classification
Abstract: In this paper, we will discuss some of the issues specifically associated to using deep convolutional neural network (CNN) in the medical image analysis setting. Recently, research shows that CNN is achieving good performance in classifying and analyzing medical images. Contrary to conventional machine learning approaches, CNN does not require the construction of hand-crafted features nor field-knowledge about the dataset. Typically, CNNs have a large number of parameters that need to be optimized in the training phase and are trained using a large number of examples (supervised learning). The requirement of a large training dataset poses a problem in medical image analysis research areas as large (balanced) disease specific dataset is difficult to achieved. This paper will discuss a few issues related to medical image analysis research including overfitting, imbalanced dataset, data augmentation and color normalization/ standardization when H&E stained histopathological images are involved.
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10:15-10:30, Paper ThBT19.2 | |
Deep Learning for Pulmonary Image Analysis: Classification, Detection, and Segmentation (I) |
Kido, Shoji | Graduate School of Science and Tech. for Innovation, Yamagu |
Hirano, Yasushi | Yamaguchi Univ |
Hashimoto, Noriaki | Yamaguchi Univ |
Mabu, Shingo | Yamaguchi Univ |
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10:30-10:45, Paper ThBT19.3 | |
Automatic Segmentation of Multiple Organs on 3D CT Images by Using a Deep Learning Approach (I) |
Zhou, Xiangrong | Gifu Univ |
Hara, Takeshi | Gifu Univ. Graduate Sch of Medicine |
Fujita, Hiroshi | Gifu Univ |
Keywords: Image segmentation, CT imaging applications, Image registration, segmentation, compression and visualization - Machine learning / Deep learning approaches
Abstract: This paper proposes a scheme for multiple organ segmentations on three-dimensional (3D) computed tomography (CT) images. A deep learning approach is used to train a detector to estimate the coordinates of the bounding box of each organ on the 3D CT scans firstly, and then train a voxel-wise classifier to segment the organ region from each bounding box. We applied this scheme to localizing and segmenting 17 types of organ regions in a dataset includes 240 CT scans. The experimental results demonstrated that our deep-learning based approach was efficient and useful in accomplishing localization and segmentation tasks for major organs on 3D CT images that scanned on different portions of the human body.
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10:45-11:00, Paper ThBT19.4 | |
Skeletal Feature Recognition and Skeletal Muscle Modeling for Skeletal Muscle Analysis in Whole-Body CT Images (I) |
Kamiya, Naoki | Aichi Prefectural Univ |
Zheng, Guoyan | Univ. of Bern |
Zhou, Xiangrong | Gifu Univ |
Muramatsu, Chisako | Gifu Univ |
Hara, Takeshi | Gifu Univ. Graduate Sch of Medicine |
Fujita, Hiroshi | Gifu Univ |
Keywords: Image segmentation, Image visualization, Image analysis and classification - Digital Pathology
Abstract: Skeletal muscles that spread throughout the body are visualized with various modalities of medical images taken for the purpose of diagnosing organs. However, skeletal muscle has large differences among intraindividual and interindividual, and its automatic recognition is one of the problems in medical image processing. In this paper, we describe the feature recognition method corresponding to the anatomical name for skeletal features closely related to skeletal muscle. Furthermore, automatic recognition of skeletal muscle based on skeletal features and muscle fiber modeling will be described. Finally, we show the application of skeletal muscle analysis using case of intractable disease ALS and future development using machine learning technique.
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11:00-11:15, Paper ThBT19.5 | |
Image Registration for Detection of Sclerotic Bone Metastasis in CT Images (I) |
Kim, Hyoungseop | Kyushu Inst. of Tech |
Lu, Huimin | Kyushu Inst. of Tech |
Tan, Joo Kooi | Kyushu Inst. of Tech |
Murakami, Seiichi | Univ. of Occupational & Environmental Health |
Aoki, Takatoshi | Univ. of Occupational and Environmental Health |
Keywords: Image registration, segmentation, compression and visualization - Machine learning / Deep learning approaches, CT imaging, Image analysis and classification - Digital Pathology
Abstract: In recent years, computer aided diagnosis (CAD) systems has been developed in medical fields. It has already become a routine work to detect abnormalities. The output from the system can be used as a second opinion to assist radiologists. Temporal subtraction technique is developed as one of the CAD system. The technique can create temporal changes from the sequential radiograph. In this paper, we propose an image registration method for enhancement of sclerotic bone metastasis regions from a current CT image to previous one. The proposed method is composed into three main steps; i) segmentation of the region of interest (ROI) using graph cut algorithms, ii) global image matching using center of gravity, and iii) final image matching based on salient region feature. We performed our method to synthesis data and real CT image with temporal changes.
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11:15-11:30, Paper ThBT19.6 | |
Decision Support System for Lung Cancer Using PET/CT and Microscopic Images (I) |
Teramoto, Atsushi | Fujita Health Univ |
Yamada, Ayumi | Fujita Health Univ |
Tsukamoto, Tetsuya | Fujita Health Univ |
Kiriyama, Yuka | Fujita Health Univ |
Tsujimoto, Masakazu | Fujita Health Univ |
Inoue, Takahiro | Fujita Health Univ |
Imaizumi, Kazuyoshi | Fujita Health Univ |
Toyama, Hiroshi | Fujita Health Univ |
Saito, Kuniaki | Fujita Health Univ |
Fujita, Hiroshi | Gifu Univ |
Keywords: PET and SPECT Imaging applications, Optical imaging and microscopy - Microscopy, Functional image analysis
Abstract: We propose the decision support system for lung cancer using positron emission tomography (PET)/computed tomography (CT) and microscopic images. Using PET/CT images, the malignancies of lung tumors were estimated based on characteristic features, the deep convolutional neural network (DCNN), and a support vector machine. In regard to the automated classification of lung cancer type, the microscope images were classified using DCNN. In the experiments, 90% of the malignant tumors were identified correctly, while 76.8% of lung cancer cells were classified correctly.
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11:15-11:30, Paper ThBT19.7 | |
Learning Sample Generation for Detecting Liver Cancer Using 3D-CNN (I) |
Mekada, Yoshito | Chukyo Univ |
Doman, Keisuke | Chukyo Univ |
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ThBT20 |
Meeting Room 325B |
Invited Session: Computational Human Models IV. Brain Stimulation (75in3) |
Invited Session |
Chair: Deng, Zhi-De | National Inst. of Mental Health |
Co-Chair: Thielscher, Axel | Copenhagen Univ. Hospital Hvidovre, Denmark & Biomedical Engineering Section |
Organizer: Makarov, Sergey | Electrical and Computer Engineering, Worcester Pol |
Organizer: Horner, Marc | ANSYS, Inc |
Organizer: Noetscher, Gregory | Worcester Pol. Inst |
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10:00-10:15, Paper ThBT20.1 | |
SimNIBS 2: A Comprehensive Pipeline for Individualized Electric Field Modeling for Transcranial Brain Stimulation (I) |
Bicalho Saturnino, Guilherme | Tech. Univ. of Denmark |
Antunes, Andre | Medtronic |
Nielsen, Jesper D. | Copenhagen Univ. Hospital Hvidovre, Denmark & Dept. of Appl |
Puonti, Oula | Copenhagen Univ. Hospital Hvidovre, Denmark & Dept. of Elec |
Madsen, Kristoffer H. | Copenhagen Univ. Hospital Hvidovre, Denmark & Dept. of Appl |
Thielscher, Axel | Copenhagen Univ. Hospital Hvidovre, Denmark & Biomedical En |
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10:15-10:30, Paper ThBT20.2 | |
Fast Multipole Method for Rapid Modeling of Transcranial Brain Stimulation Problems (I) |
Makarov, Sergey | Electrical and Computer Engineering, Worcester Pol |
Noetscher, Gregory | Worcester Pol. Inst |
Raij, Tommi | Northwestern Univ. Inst. of Neruoscience |
Nummenmaa, Aapo | Massachussetts General Hospital |
Keywords: Models of therapeutic devices and systems, Computer modeling for treatment planning, Computer model-based assessments for regulatory submissions
Abstract: Near real-time modeling of intracranial electric fields generated during non-invasive brain stimulation is a capability that would enable coil navigation, stimulation planning and post-hoc validation. Traditional methods of modeling field distributions over high resolution head models require simulation times that are far beyond those necessary for online applications. This study presents a novel Boundary Element Method framework that has been dramatically accelerated using the Fast Multipole Method. Initial results show comparable to superior resolution as compared with standard Finite Element Method with significantly faster runtimes.
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10:30-10:45, Paper ThBT20.3 | |
Electric Field Induced by Electroconvulsive Therapy in Patients with Major Depression (I) |
Deng, Zhi-De | National Inst. of Mental Health |
Fridgeirsson, Egill Axfjord | Department of Psychiatry, Acad. Medical Center, Amsterdam |
Lilien, Joseph | Duke Univ |
van Wingen, Guido | Acad. Medical Center Amsterdam |
Van Waarde, Jeroen Antonius | Rijnstate Hospital |
Keywords: Neural stimulation (including deep brain stimulation), Models of therapeutic devices and systems, Neuromodulation devices
Abstract: This study aimed to characterize the induced electric field distributions in a population of patient who received bilateral and/or unilateral electroconvulsive therapy for the treatment of depression. We observed approximately 22% variation in the maximum electric field strength induced in the brain due to interindividual differences in head anatomy. Finally, we identified a cluster of white matter voxels where the electric field strength is correlated with treatment outcome.
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10:45-11:00, Paper ThBT20.4 | |
Head Models for Computing Brain Electrical Fields in Transcranial Stimulation (I) |
Bai, Siwei | Tech. Univ. of Munich |
Loo, Colleen | School of Psychiatry, Univ. of New South Wales |
Martin, Donel | School of Psychiatry, Univ. of New South Wales |
Dokos, Socrates | Univ. of New South Wales |
Keywords: Models of therapeutic devices and systems, Neuromodulation devices, Computer modeling for treatment planning
Abstract: Extensive clinical research has shown that the efficacy and cognitive outcomes of electroconvulsive therapy (ECT) are determined, in part, by the chosen electrode placement. Although the three conventional placements have shown significant efficacy, they also have their disadvantages. This study examines eight unconventional or new ECT placements, including LART, using computational head models in order to optimise ECT treatment.
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11:00-11:15, Paper ThBT20.5 | |
Integrating Accurate Neuronal Models with Electric Field Simulations of Transcranial Brain Stimulation (I) |
Aberra, Aman | Duke Univ |
Grill, Warren | Duke Univ |
Peterchev, Angel V | Duke Univ |
Keywords: Neural stimulation (including deep brain stimulation), Medical devices interfacing with the brain or nerves
Abstract: We developed a model of transcranial-stimulation-induced neuronal activation by coupling realistic, multi-compartmental models of cortical neurons to a finite element method model of the human head derived from magnetic resonance images. This multi-scale model enabled quantification of neural activation in layer-specific populations of cortical cells with arbitrary pulse waveforms and E-field distributions.
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11:15-11:30, Paper ThBT20.6 | |
Electric Field Induced by Repetitive Transcranial Magnetic Stimulation in Patients with Major Depression (I) |
Deng, Zhi-De | National Inst. of Mental Health |
Liston, Conor | Weill Cornell Medicine |
Gunning, Faith | Weill Cornell Medicine |
Dubin, Marc | Weill Cornell Medical Coll |
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ThCT1 |
Meeting Room 311 |
Sensory Neuroprostheses (Theme 6) |
Oral Session |
Chair: Suaning, Gregg | The Univ. of Sydney |
Co-Chair: Weiland, James | Univ. of Michigan |
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13:30-13:45, Paper ThCT1.1 | |
An Investigation of the Effect of AGC Gain on the Output Signal to Noise Ratio in Cochlear Implant Sound Processing |
Watkins, Gregory Douglas | Sydney Univ |
Swanson, Brett Anthony | Cochlear Limited |
Suaning, Gregg | The Univ. of Sydney |
Keywords: Sensory neuroprostheses, Sensory neuroprostheses - Auditory
Abstract: Measurement of speech intelligibility of cochlear implant (CI) recipients is typically carried out with a speech-in-noise test procedure. Metrics which predict speech intelligibility can pre-screen new sound processing strategies prior to comprehensive testing with human subjects. The Output Signal to Noise Ratio (OSNR) metric calculates the Signal to Noise Ratio (SNR) which is present at the CI sound processor output. Watkins et al. (2018) found OSNR was an accurate predictor of speech intelligibility that could predict intelligibility in scenarios where other predictors could not. The current study investigated the effect of the sound processor automatic gain control (AGC) on OSNR and a simplified metric, Separate gain SNR (SSNR), which calculated the SNR at the CI output, assuming no interaction between the signal and noise in the sound processor. Prediction accuracy of OSNR was compared to that of Input SNR and SSNR. It was found that AGC-induced distortion and SNR degradation in speech gaps worsened OSNR. For scenarios with significant non-linear, time-varying processing, OSNR was the most accurate prediction metric. SSNR was found to be an inaccurate predictor.
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13:45-14:00, Paper ThCT1.2 | |
Noise-Induced Hearing Loss in Mice: Effects of High & Low Levels of Noise Trauma in CBA Mice |
Amanipour, Reza | Univ. of South Florida |
Zhu, Xiao Xia | Univ. of South Florida |
Duvey, Guillaume | Pragma Therapeutics |
Celanire, Sylvain | Pragma Therapeutics |
Walton, Joseph | Univ. of South Florida |
Frisina, Robert | Univ. of South Florida |
Keywords: Sensory neuroprostheses - Auditory, Brain physiology and modeling - Sensory-motor, Neurological disorders - Treatment methodologies
Abstract: Acoustic trauma can induce temporary or permanent noise-induced hearing loss (NIHL). Noise exposed animal models allow us to study the effects of various noise intensity levels on the cochlea and auditory pathways. Here we studied the short-term and long-term functional changes occurring in the auditory system following exposure to two different noise traumas. Several measures of hearing function known to change following noise exposure were examined: Temporary (TTS) and permanent (PTS) threshold shifts were measured using auditory brainstem responses (ABR), outer hair cell function was examined using distortion product otoacoustic emissions (DPOAEs), and auditory temporal processing was assessed using a gap-in-noise ABR paradigm. Physiological measures were made before and after the exposure (24 hours, 2 weeks, 4 weeks, and 1 year). The animals were perfused and their brain, and cochlea were collected for future biomarker studies. Mice were exposed to 110 dB and 116 dB received octave-band noise levels for 45 minutes, and both groups demonstrated significant threshold shifts 1 day post-noise exposure across all frequencies. However 2 weeks post-exposure, PTS within the 110 dB group was significantly reduced compared to 1 day post trauma, this improvement in thresholds was not as great in the 116 dB exposure group. At 2 weeks post-trauma, differences between the measured PTS in the two groups was significant for 4 of the 7 measured frequencies. 1 year after exposure mice in the 110 group showed very minor PTS, but the 116 group animals showed a large PTS comparable to their 2 and 4 week PTS. At this time point, PTS variation between the two groups was significant across all frequencies. DPOAE amplitudes measured 2 weeks post exposure showed recovery for all frequencies within 10 dB (average) of the baseline in the 110 dB group, however for the 116 dB exposure DP amplitudes were elevated by about 30 dB. The differences in DPOAE amplitudes between the 110 dB and 116 d
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14:00-14:15, Paper ThCT1.3 | |
Recovery of the Response of Sensory Fibers to the Second of a Pair of Peripheral Nerve Stimuli |
Brunton, Emma Kate | Newcastle Univ |
Silveira, Carolina | Newcastle Univ |
Ridell, John | Univ. of Glasgow |
Nazarpour, Kianoush | Newcastle Univ |
Keywords: Sensory neuroprostheses, Motor neuroprostheses
Abstract: Neural interfaces that stimulate the peripheral nerves have the potential to provide sensory feedback from artificial hands. Many neural interfaces are now being developed that allow for multi-channel stimulation of the nerves. It is widely accepted that the electric fields generated by two or more contacts on a neural interface can interact. However, this has previously not been examined in the context of sensory feedback prostheses. Here, we aimed to investigate these interactions and the recovery dynamics of the sensory fibers. A multi-channel cuff electrode was implanted on the sciatic nerve of a rat. It comprised of four rings (1 mm apart), each containing four circumferentially arranged electrodes. Temporally-patterned pairs of electrical stimuli were delivered through all 120 combinations of electrode pairs. Compound action potentials, elicited by stimulation of the sciatic nerve, were measured with two pairs of hook electrodes placed on the L4 dorsal root. We find that regardless of the relative position of the two electrodes on the cuff, at an interval of 0 ms, the CAP response is facilitated. At all other intervals, an inter-stimulus interval of even 5 ms was not enough for the response to the second stimulus to fully recover. This observation suggests that overlapping regions of nerve were stimulated. Examining only the intervals where the CAP did not fully recover, we noticed that if the electrodes lay longitudinally, that is, along the nerve, the CAP recovery was significantly impaired, compared to when the electrodes were in any other relative position. The observed space- and time-dependent interactions advocate for further controlled neuroscience studies in parallel to translational work on closed-loop prosthesis control.
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14:15-14:30, Paper ThCT1.4 | |
Normalized Transfer Entropy As a Tool to Identify Multisource Functional Epileptic Networks |
Kale, Poojitha | Penn State Univ |
Acharya, Vinita | Penn State Univ |
Acharya, Jayant | Penn State Univ |
Subramanian, Thyagarajan | Penn State Univ |
Almekkawy, Mohamed | Penn State Univ |
Keywords: Sensory neuroprostheses - Signal and vision processing, Neurological disorders - Epilepsy, Neural signals - Information theory
Abstract: Epilepsy is a major health problem worldwide. A significant proportion of patients develop medication-refractory epilepsy (MRE); they are often evaluated for possible surgery where the focus of epileptogenic zones (EZ) are removed from the brain. Hence, prior to epilepsy surgery, insertion of depth electrodes into the brain is necessary to identify the EZs. These depth electrodes have multiple contacts that monitor the neuronal activity in multiple locations within the brain along each electrode trajectory. In the present study, we show that normalized transfer entropy measurements demonstrate functional connectivity across multiple sites within the brain of an MRE patient who did not demonstrate a clear EZ using conventional EEG criteria. Interestingly, linear measures of functional connectivity were not predictive of such an epileptic network. Our results suggest that routine evaluation of both linear and non-linear functional connectivity including normalized transfer entropy from depth electrode recordings may be useful to identify multisource epileptogenic networks in MRE patients. Identification of networks that contribute to epilepsy in such patients could potentially allow the clinician to avoid resective surgery and adopt alternate therapies such as vagal nerve stimulation or other emergent alternatives.
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14:30-14:45, Paper ThCT1.5 | |
Electrical Field Shaping Techniques in a Feline Model of Retinal Degeneration |
Spencer, Thomas | Bionics Inst |
Fallon, James | Bionics Inst |
Abbott, Carla | Centre for Eye Res. Australia |
Allen, Penelope J | Royal Victorian Eye and Ear Hospital |
Brandli, Alice | Centre for Eye Res. Australia |
Luu, Chi | Centre for Eye Res. Australia |
Epp, Stephanie | Bionics Inst |
Shivdasani, Mohit N. | Univ. of New South Wales |
Keywords: Sensory neuroprostheses - Visual, Neural stimulation, Neural signal processing
Abstract: The majority of preclinical studies investigating multi-electrode field shaping stimulation strategies for retinal prostheses, have been conducted in normally-sighted animals. This study aimed to reassess the effectiveness of two electrical field shaping techniques that have been shown to work in healthy retinae, in a more clinically relevant animal model of photoreceptor degeneration. Four cats were unilaterally blinded via intravitreal injections of adenosine triphosphate. Cortical responses to traditional monopolar (MP) stimulation, focused multipolar (FMP) stimulation and two-dimensional current steering were recorded. Contrary to our previous work, we found no significant difference between the spread of cortical activation elicited by FMP and MP stimulation, and we were not able to reproduce cortical responses to single-electrode retinal stimulation using two-dimensional current steering. These findings suggest that while shown to be effective in normally-sighted animals, these techniques may not be readily translatable to patients with retinal degeneration and require further optimization.
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14:45-15:00, Paper ThCT1.6 | |
Optic Nerve and Retinal Electrostimulation in Rats: Direct Activation of the Retinal Ganglion Cells |
Barriga-Rivera, Alejandro | Univ. Pablo De Olavide |
Suaning, Gregg | The Univ. of Sydney |
Delgado-Garcia, Jose Maria | Univ. Pablo De Olavide |
Gruart, Agnes | Univ. Pablo De Olavide |
Keywords: Sensory neuroprostheses - Visual, Neural stimulation, Sensory neuroprostheses
Abstract: Visual prosthesis is competing with biological approaches to restore vision to the blind. Understanding and developing the ability to replicate the neural code of the retina are key factors that can bring bionic vision significant advantage. Here, electrically evoked potentials were recorded in anesthetized rats from the dorsal surface of the superior colliculus. Electrical stimuli of different amplitudes were delivered at the retina and the optic nerve. An evoked potential appeared in both cases within the first 5 ms post-stimulus suggesting that this component of the response was initiated by direct activation of the retinal ganglion cells. However, in the case of retinal neurostimulation, a second evoked potential occurred 9.0 ± 3.4 ms after the stimulus delivery. Because this component was not present in the case of optic nerve electrostimulation, it is expected to be originated by the activation of other cells in the retinal network.
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ThCT2 |
Meeting Room 312 |
Independent and Principal Component Analysis (Theme 1) |
Oral Session |
Chair: Lubecke, Victor | Univ. of Hawaii Manoa |
Co-Chair: Boric-Lubecke, Olga | Univ. of Hawaii Manoa |
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13:30-13:45, Paper ThCT2.1 | |
Supervised Bayesian Source Separation of Nonlinear Mixtures for Quantitative Analysis of Gas Mixtures |
Madrolle, Stéphanie | Univ. Grenoble Alpes, CEA, LETI, Minatec Campus, F-38054 Grenobl |
Duarte, Leonardo | Univ. of Campinas |
Grangeat, Pierre | Univ. Grenoble, Alpes, CEA, LETI, MINATEC CAMPUS |
Jutten, Christian | Univ. of Grenoble |
Keywords: Independent component analysis, Data mining and processing in biosignals, Signal pattern classification - Markov models
Abstract: In medical applications, quantitative analysis of breath may open new prospects for diagnosis or for patient monitoring. To detect acetone, a breath biomarker for diabetes, we use a single metal-oxide (MOX) gas sensor working in a dual temperature mode. We propose a linear-quadratic model to describe the mixing model mapping gas concentrations to MOX sensor responses. In this purpose, it is necessary to inverse the nonlinear problem in order to quantify the component of the gas mixture. As a proof of concept, we study a mixture of two gases, acetone and ethanol diluted in air buffer. In order to estimate the concentration of each gas, we introduce a supervised Bayesian source separation method. Based on MCMC stochastic sampling methods to estimate the mean of the posterior distribution, this Bayesian approach is robust to noise for solving this ill-posed non-linear inversion problem. We analyze the performance on a set of samples associated with a set of gas concentration covering the range suitable for exhaled breath. We use a cross-validation approach, calibrating the mixing parameters with some samples and validating the source estimation with others. Our new supervised method applied on a linear-quadratic model allows to estimate acetone and ethanol concentration with a precision of around 2 ppm.
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13:45-14:00, Paper ThCT2.2 | |
Separation of Respiratory Signatures for Multiple Subjects Using Independent Component Analysis with the JADE Algorithm |
Islam, Shekh Md Mahmudul | Univ. of Hawaii at Manoa, Hawaii, USA |
Yavari, Ehsan | Univ. of Hawaii Manoa |
Rahman, Ashikur | Univ. of Hawaii at Manoa |
Lubecke, Victor | Univ. of Hawaii Manoa |
Boric-Lubecke, Olga | Univ. of Hawaii Manoa |
Keywords: Principal and independent component analysis - Blind source separation, Independent component analysis, Principal component analysis
Abstract: Respiration monitoring using microwave Doppler radar has attracted significant interest over the last four decades due to its non-invasive and non-contact form of measurement. However, this technology is still not at the level of practical implementations in healthcare due to motion artifacts and interference from multiple subjects within the range of Doppler radar sensor. Most reported results in literature focus only on single subject measurements because when multiple subjects are present there are interfering respiration signals which are difficult to separate as individual respiration signals. This paper investigates the feasibility of separating respiratory signatures from the multiple subjects. We employed a new approach using Independent Component Analysis (ICA) with the Joint Approximate Diagonalization of Eigenmatrices (JADE) algorithm to achieve this for closely spaced subjects, and the system is also capable of estimating Direction of Arrival (DOA) for well-spaced subjects. Experimental results demonstrated that ICA-JADE method can separate respiratory signatures from two subjects one meter apart from each other at a distance from the radar of 2.89 meters. The separated respiratory pattern closely correlates with reference chest belt respiration patterns, and the mean square error is approximately 11.58%. Concisely, this paper clearly demonstrates that by integrating ICA with the JADE algorithm in Doppler radar physiological monitoring system, multiple subjects can be monitored simultaneously.
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14:00-14:15, Paper ThCT2.3 | |
Removal of Electrocardiogram Interference from Diaphragmatic Electromyogram Signals Using Sliding Singular Spectrum Analysis |
Saeed, Muzammil | London South Bank Univ |
Alty, Steve | Royal Holloway, Univ. of London |
Keywords: Physiological systems modeling - Signal processing in physiological systems, Independent component analysis, Principal and independent component analysis - Blind source separation
Abstract: Over recent years, Singular Spectrum Analysis (SSA) has gained popularity as an effective means to denoise biologically sourced single channel signals, especially Electromyogram (EMG) and Electrocardiogram (ECG) signals amongst others. There are numerous applications whereby the signal acquisition process results in the mixing of both types of signals along with body motion artifacts and the inevitable electromagnetic interference. Both ECG and EMG signals are very useful to physicians, though preferably in isolation, though they rarely present themselves in this manner. Simple filtering techniques are ineffective in their separation as both signal spectra overlap in the frequency domain. In this paper, we propose a technique based on a sliding SSA algorithm which proves to be more successful in separating real mixed EMG and ECG signals than traditional block based approaches on single channel data. SSA is a non-parametric technique that decomposes the original time series into a number of additive components, each of which can then be readily identified based on statistical analysis as belonging to EMG or ECG signals. This approach could be applied equally to other signal types using different statistical methods as required, moreover, this technique is relatively straight-forward to implement and does not require any reference signals or training.
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14:15-14:30, Paper ThCT2.4 | |
Evaluation of Artifact Subspace Reconstruction for Automatic EEG Artifact Removal |
Chang, Chi-Yuan | Univ. of California, San Diego |
Hsu, Sheng-Hsiou | Univ. of California, San Diego |
Pion-Tonachini, Luca | Univ. of California, San Diego |
Jung, Tzyy-Ping | Univ. of California San Diego |
Keywords: Principal and independent component analysis - Blind source separation
Abstract: One of the greatest challenges that hinder the decoding and application of electroencephalography (EEG) is that EEG recordings almost always contain artifacts – non-brain signals. Among existing automatic artifact-removal methods, artifact subspace reconstruction (ASR) is an online and realtime capable, component-based method that can effectively remove transient or large-amplitude artifacts. However, the effectiveness of ASR and the optimal choice of its parameter have not been evaluated and reported, especially on real EEG data. This study systematically validates ASR on ten EEG recordings in a simulated driving experiment. Independent component analysis (ICA) is applied to separate artifacts from brain signals to allow a quantitative assessment of ASR’s effectiveness in removing various types of artifacts and preserving brain activities. Empirical results show that the optimal ASR parameter is between 10 and 100, which is small enough to remove activities from artifacts and eye-related components and large enough to retain signals from brain-related components. With the appropriate choice of the parameter, ASR can be a powerful and automatic artifact removal approach for offline data analysis or online real-time EEG applications such as clinical monitoring and brain-computer interfaces.
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14:30-14:45, Paper ThCT2.5 | |
Dimensionality Reduction Based Transfer Learning Applied to Pharmacogenomics Databases |
Dhruba, Saugato Rahman | Texas Tech. Univ |
Rahman, Raziur | Texas Tech. Univ |
Matlock, Kevin | Texas Tech. Univ |
Ghosh, Souparno | Texas Tech. Univ |
Pal, Ranadip | Texas Tech. Univ |
Keywords: Principal component analysis, Data mining and processing in biosignals
Abstract: Recent years have observed a number of Pharmacogenomics databases being published that enable testing of various predictive modeling techniques for personalized therapy applications. However, the consistencies between the databases are usually limited in spite of having significant number of common cell lines and drugs. In this article, we consider the problem of whether we can use the model learned from one secondary database to improve the prediction for the other target database. We illustrate using two pharmacogenomics databases that representing the databases using common basis vectors can improve prediction performance as compared to the naive application of a model trained on one database to another. We also elucidate the robustness of using PCA based basis vectors for scenarios with low correlated input features.
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14:45-15:00, Paper ThCT2.6 | |
Introducing a Combination of ICA-EMD to Suppress Muscle and Ocular Artifacts in EEG Signals |
Santillan Guzman, Alina | Benemérita Univ. Autónoma De Puebla |
Oliveros Oliveros, José Jacobo | Benemérita Univ. Autónoma De Puebla |
Morín Castillo, María Monserrat | Benemérita Univ. Autónoma De Puebla |
Keywords: Independent component analysis, Time-frequency and time-scale analysis - Empirical mode decomposition in biosignal analysis, Adaptive filtering
Abstract: This paper presents a combination of Independent Component Analysis (ICA) with Empirical Mode Decomposition (EMD) to suppress muscle and ocular artifacts in electroencephalographic (EEG) signals: By means of ICA, the EEG signals are decomposed into independent components. To avoid the suppression of artifactual components still containing physiological information, EMD is applied to decompose the components in Intrinsic Mode Functions (IMFs). The IMFs with mainly muscle artifacts are removed, and a new data set of independent components without muscle artifacts is generated. From this set, the components containing ocular artifacts are suppressed and clean data are reconstructed. In this way, the muscle and ocular artifacts are better suppressed than using pure ICA, or pure EMD. The performance of the proposed combination is applied to a semi-simulated data set, and three real EEG data sets from healthy subjects contaminated with both artifacts.
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ThCT3 |
Meeting Room 314 |
Deep Learning Imaging (I) (Theme 2) |
Oral Session |
Chair: Spasov, Simeon | Univ. of Cambridge |
Co-Chair: Du, Yiping | Shanghai Jiao Tong Univ |
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13:30-13:45, Paper ThCT3.1 | |
Joint and Deep Ensemble Regression of Clinical Scores for Alzheimer’s Disease Using Longitudinal and Incomplete Data |
Lei, Baiying | Shenzhen Univ |
Yang, Mengya | Shenzhen Univ |
Hou, Wen | Shenzhen Univ |
Yang, Peng | Shenzheng Univ |
Li, Xia | Shenzhen Univ |
Wang, Tianfu | Shenzhen Univ |
Zou, Wenbin | Shenzhen Univ |
Elazab, Ahmed | Shenzhen Univ |
Keywords: Image analysis and classification - Machine learning / Deep learning approaches, Image feature extraction, Brain imaging and image analysis
Abstract: Alzheimer’s disease (AD) is a neurodegenerative disease with an irreversible and progressive process, and thus close monitoring is essential for making adjustments in the treatment plan. Since clinical scores can indicate the disease status effectively, the prediction of the scores based on the magnetic resonance imaging (MRI) data is highly desirable. Different from previous studies at a single time point, we propose to build a model to explore the relationship between MRI data and scores, thereby predicting longitudinal scores at future time points from the corresponding MRI data. The model incorporates three parts, correntropy regularized joint learning based feature selection, deep polynomial network based feature encoding and finally, support vector regression. The regression process is carried out for two scenarios. One is to use baseline data for predictions at future time points, and the other is to combine all the previous data for the prediction at the next time point. Meanwhile, the missing scores are filled in the second scenario to address the incompleteness presented in the data. The simulation results validate that the proposed model describes accurately the relationship between MRI data and scores, and thus is effective in predicting longitudinal scores.
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13:45-14:00, Paper ThCT3.2 | |
Filter-Pruned 3D Convolutional Neural Network for Drowsiness Detection |
Yao, Heming | Univ. of Michigan |
Zhang, Wei | DENSO International America |
Malhan, Rajesh | DENSO International America |
Gryak, Jonathan | Univ. of Michigan |
Najarian, Kayvan | Univ. of Michigan - Ann Arbor |
Keywords: Image analysis and classification - Machine learning / Deep learning approaches
Abstract: Drowsiness is an important human attention status and an efficient drowsiness detection monitoring and alarm system can be used for drivers, large vehicle operators, aircraft pilots, etc. In this study, we developed a visual-based drowsiness detection system that can analyze videos and make predictions on human attention status. A 3D convolutional neural network (CNN) was built for spatio-temporal feature extraction in consecutive frames, and temporal smoothing was used as a post-processing method to remove noisy predictions. As a part of an assistance system, a real-time, lightweight and computationally-efficient system is preferable. Thus, we proposed a Scale Module that can be easily integrated into the convolutional layer and estimate the importance of filters. Our results show that the scale values calculated from the Scale Module are good indicators for filter pruning, and that filters with a small value of scale can be removed with negligible loss in the model's performance.
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14:00-14:15, Paper ThCT3.3 | |
Skin Lesion Analysis by Multi-Target Deep Neural Networks |
Yang, Xulei | Inst. for Infocomm Res. A*STAT |
Li, Hangxing | Student |
Wang, Li | Inst. for Infocomm Res. Agency for Science, Tech |
Yeo, Si Yong | Inst. of High Performance Computing |
Su, Yi | Inst. of High Performance Computing |
Zeng, Zeng | Employer |
Keywords: Image analysis and classification - Machine learning / Deep learning approaches, Image segmentation, Image classification
Abstract: Automatic skin lesion analysis involves two critical steps: lesion segmentation and lesion classification. In this work, we propose a novel multi-target deep convolutional neural network (DCNN) to simultaneously tackle the problem of segmentation and classification. Based on U-Net and GoogleNet, a single model is constructed with three different targets of both lesion segmentation and two independent binary lesion classifications (i.e., melanoma detection and seborrheic keratosis identification), aiming to explore the differences and commonalities over different target models. We conduct experiments on dermoscopic images from the International Skin Imaging Collaboration (ISIC) 2017 Challenge. Results of our multi-target DCNN model demonstrates superiority over single model with one target only (such as U-net or GoogleNet), indicating its learning efficiency and potential for application in automatic skin lesion diagnosis. To the best of our knowledge, this work is the first demonstration for a single end-to-end deep neural network model that simultaneously handle both segmentation and classification in the field of skin lesion analysis.
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14:15-14:30, Paper ThCT3.4 | |
A Deep Unsupervised Learning Approach Toward MTBI Identification Using Diffusion MRI |
minaee, shervin | New York Univ |
Wang, Yao | Pol. Inst. of New York Univ |
Choromanska, Anna | NYU Tandon |
Chung, Sohae | NYU School of Medicine |
Wang, Xiuyuan | NYU School of Medicine |
Fieremans, Els | New York Univ. School of Medicine |
Flanagan, Steven | New York Univ. School of Medicine |
Rath, Joseph | New York Univ. School of Medicine |
Lui, Yvonne | NYU School of Medicine |
Keywords: Image analysis and classification - Machine learning / Deep learning approaches, Image feature extraction, Image classification
Abstract: Mild traumatic brain injury is a growing public health problem with an estimated incidence of over 1.7 million people annually in US. Diagnosis is based on clinical history and symptoms, and accurate, concrete measures of injury are lacking. This work aims to directly use diffusion MR images obtained within one month of trauma to detect injury, by incorporating deep learning techniques. To overcome the challenge due to limited training data, we describe each brain region using the bag of word representation, which specifies the distribution of representative patch patterns. We apply a convolutional auto-encoder to learn the patch-level features, from overlapping image patches extracted from the MR images, to learn features from diffusion MR images of brain using an unsupervised approach. Our experimental results show that the bag of word representation using patch level features learnt by the auto encoder provides similar performance as that using the raw patch patterns, both significantly outperform earlier work relying on the mean values of MR metrics in selected brain regions.
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14:30-14:45, Paper ThCT3.5 | |
A Multi-Modal Convolutional Neural Network Framework for the Prediction of Alzheimer’s Disease |
Spasov, Simeon | Univ. of Cambridge |
Passamonti, Luca | Univ. of Cambridge |
Duggento, Andrea | Univ. of Rome "Tor Vergata" |
Liò, Pietro | Univ. of Cambridge |
Toschi, Nicola | Univ. of Rome "Tor Vergata", Faculty of Medicine |
Keywords: Image analysis and classification - Machine learning / Deep learning approaches, Image analysis and classification - Digital Pathology, Brain imaging and image analysis
Abstract: This paper presents a multi-modal Alzheimer’s disease (AD) classification framework based on a convolutional neural network (CNN) architecture. The devised model takes structural MRI, and clinical assessment and genetic (APOe4) measures as inputs. Our CNN structure is designed to be efficient in its use of parameters which reduces overfitting, computational complexity, memory requirements and speed of prototyping. This is achieved by factorising the convolutional layers in parallel streams which also enables the simultaneous extraction of high and low level feature representations. Our method consistently achieves high classification results in discriminating between AD and control subjects with an average of 99% accuracy, 98% sensitivity, 100% specificity and an AUC of 1 across all test folds. Our study confirms that careful tuning of CNN characteristics can result in a framework which delivers extremely accurate predictions in a clinical problem despite data paucity, opening new avenues for application to prediction tasks which regard patient stratification, prediction of clinical evolution and eventually personalised medicine applications.
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14:45-15:00, Paper ThCT3.6 | |
Left Ventricle Segmentation in Cardiac MR Images Using Fully Convolutional Network |
Nasr-Esfahani, Mina | Isfahan Univ. of Tech |
Mohrekesh, Majid | Isfahan Univ. of Tech |
Akbari, Mojtaba | Isfahan Univ. of Tech |
Soroushmehr, S.M.Reza | Univ. of Michigan, Ann Arbor |
NasrEsfahani, Ebrahim | Isfahan Univ. of Tech |
Karimi, Nader | Isfahan Univ. of Tech |
Samavi, Shadrokh | McMaster Univ |
Najarian, Kayvan | Univ. of Michigan - Ann Arbor |
Keywords: Image registration, segmentation, compression and visualization - Machine learning / Deep learning approaches
Abstract: Medical image analysis, especially segmenting a specific organ, has an important role in developing clinical decision support systems. In cardiac magnetic resonance (MR) imaging, segmenting the left and right ventricles helps physicians diagnose different heart abnormalities. There are challenges for this task, including the intensity and shape similarity between the left ventricle and other organs, inaccurate boundaries, and presence of noise in most of the images. In this paper, we propose an automated method for segmenting the left ventricle in cardiac MR images. We first automatically extract the region of interest and then employ it as an input of a fully convolutional network. We train the network accurately despite the small number of left ventricle pixels in comparison with the whole image. Thresholding on the output map of the fully convolutional network and selection of regions based on their roundness are performed in our proposed post-processing phase. The Dice score of our method reaches 87.24% by applying this algorithm on the York dataset of heart images.
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ThCT4 |
Meeting Room 315 |
Bio-Electric Sensors (Theme 7) |
Oral Session |
Chair: Krishnan, Ashwati | Carnegie Mellon Univ |
Co-Chair: Pei, Weihua | Inst. of Semiconductors, CAS |
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13:30-13:45, Paper ThCT4.1 | |
Simple, Fast and Highly Sensitive Detection of Gram-Negative Bacteria by a Novel Electrical Biosensor |
Wu, Jie | The Univ. of Tennessee |
cheng, cheng | The Univ. of Tennessee |
Yuan, Quan | The Univ. of Tennessee |
Oueslati, Rania | The Univ. of Tennessee |
Zhang, Jian | Hefei Univ. of Tech |
Chen, Jiangang | The Univ. of Tennessee |
almeida, Raul | The Univ. of Tennessee |
Keywords: Chemo/bio-sensing - Biological sensors and systems, Bio-electric sensors - Sensing methods, Chemo/bio-sensing - Techniques
Abstract: This work presents a rapid, low-cost, highly sensitive and specific capacitive sensor for detection of Gram negative bacteria in a field setting. Recognition of Gram-negative bacteria is based on specific detection of lipopolysaccharides (LPS) by LPS-specific aptamer probe immobilized on electrode sensors. An inhomogeneous AC electric field is applied on sensor electrodes and induces positive dielectrophoresis that attracts bacteria to the sensor electrodes for rapid detection. The same AC signal is also used to detect the binding reactions occurred on the sensor surface. The AC signal was optimized, and the binding between LPS and the specific aptamer was demonstrated. The detection limit reaches as low as 4.9 fg/mL for free LPS molecules and 276#/mL of bacteria within a 30s’ response time, meeting the needs of on-site bacteria detection.
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13:45-14:00, Paper ThCT4.2 | |
An Exploration of Behind-The-Ear ECG Signals from a Single Ear Using Inkjet Printed Conformal Tattoo Electrodes |
Jacob, Nikhil Kurian | Univ. of Manchester |
Balaban, Ertan | The Univ. of Manchester |
Saunders, Rachel Elizabeth | Univ. of Manchester |
Batchelor, John | Univ. of Kent |
yeates, stephen | Univ. of Manchester |
Casson, Alexander James | The Univ. of Manchester |
Keywords: Bio-electric sensors - Sensor systems, Wearable body-compliant, flexible and printed electronics, Physiological monitoring - Instrumentation
Abstract: Wearable sensors placed behind-the-ear are emerging as being very promising for unobtrusive long term monitoring. Factors such as gait, electroencephalography (EEG), and ballistocardiography (BCG) can all be measured from behind-the-ear in a socially acceptable hearing aid based form factor. Previous works have investigated the recording of electrocardiography (ECG) from the ear, but generally with one electrode placed some distance away from the ear itself. This paper uses recently introduced tattoo electrodes to investigate whether ECG components can indeed be measured from behind a single ear. Compared to a reference photophelsmography (PPG) device we show that the fundamental heart beat frequency is present in behind-the-ear ECG only in half of the cases considered. In contrast the second harmonic is present in all records and could allow the extraction of heart rate to within a few beats-per-minute accuracy. Further signal processing work is required to allow the automated extraction of this, particularly when working with short time windows of data, but our results characterize the signal and demonstrate the principle of behind-the-ear ECG collected from a single ear.
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14:00-14:15, Paper ThCT4.3 | |
Low-Cost Carbon Fiber-Based Conductive Silicone Sponge EEG Electrodes |
Krishnan, Ashwati | Carnegie Mellon Univ |
Kumar, Ritesh | Carnegie Mellon Univ |
Venkatesh, Praveen | Carnegie Mellon Univ |
Kelly, Shawn | Carnegie Mellon Univ |
Grover, Pulkit | Carnegie Mellon Univ |
Keywords: New sensing techniques, Bio-electric sensors - Sensing methods, Wearable body sensor networks and telemetric systems
Abstract: We propose a novel carbon fiber-based conductive silicone sponge for low electrode-skin impedance EEG recordings. When this sponge is used with water or saline solution, no gel is required, lowering the setup time drastically compared to classical wet electrodes. Moreover, the wet conductive carbon fiber silicone sponges achieve an electrode-skin impedance as low as 2.5kOhms at 1kHz when wet, making them better than state of the art gel electrodes. Additionally, even as the sponge dries out, it continues to remain conductive and performs as a reliable dry electrode. We demonstrate through experiments that these conductive carbon fiber silicone sponge electrodes, wet or dry, are able to measure alpha wave activity. Our carbon fiber conductive sponge electrodes are low-cost and are highly suitable for designs of portable high density EEG measurement systems.
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14:15-14:30, Paper ThCT4.4 | |
Increased Conductivity and Reduced Settling Time of Carbon-Based Electrodes by Addition of Sea Salt for Wearable Application |
Noh, Yeon Sik | Univ. of Massachusetts Amherst |
Ye, Xiang | Univ. of Connecticut |
Murphy, Laura | Univ. of Connecticut |
Eaton-Robb, Caitlin | Univ. of Connecticut |
Dimitrov, Tanya | Univ. of Connecticut |
Choi, Woo Jung | Boston Univ |
Chon, Ki | Univ. of Connecticut |
Keywords: Bio-electric sensors - Sensing methods, Bio-electric sensors - Sensor systems
Abstract: A carbon-based dry electrode is designed to measure bio-potential from skin surface without hydrogel. Consequently, unlike Ag/AgCl electrodes, the carbon-based electrodes require some settling time before a high-fidelity signal is obtained due to the process for impedance matching among skin surface, electrode and amplifiers in biometric system. Besides, especially, when electrocardiogram (ECG) is measured at some distance away from the chest using carbon-based electrodes for wearable application, the settling time could be a critical concern for immediate data collection due to the smaller bio-potential and bigger motion artifact noises. The settling time was defined as the time it takes for the carbon-based electrodes to have the same impedance as that of Ag/AgCl electrodes at a particular frequency (< 1 kHz) for bio-signals. In this study, we investigated the characteristics of the skin contact impedance as a function of time using carbon-based electrodes with and without sea salt and different thickness. Specifically, sea salt was added to the carbon black (SCB)/polydimethlysiloxane (PDMS) electrode to examine the level of enhanced conductivity and reduction of settling time. We used SCB/PDMS and CB/PDMS electrodes with thickness of 1.0 mm and 1.5 mm, examined their electrode and skin contact impedance values and compared them to Ag/AgCl electrodes. We collected impedance data from seven subjects using both SCB and CB/PDMS electrodes every 10 minutes for 50 minutes. A SCB/PDMS electrode showed lower impedance than a CB/PDMS electrode, and for both types of electrodes, higher thickness resulted in lower impedance. The same results were found for skin contact impedance. The settling times of the SCB/PDMS electrodes were found to be 20 ± 10 minutes and 40 ± 10 minutes for widths of 1.0 mm and 1.5 mm, respectively. The settling time for CB/PDMS without sea salt resulted in significantly higher settling time (> 50 minutes) when compared to SCB/PDMS electrodes.
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14:30-14:45, Paper ThCT4.5 | |
Design of High-Density Electrodes for EEG Acquisition |
Xing, Xiao | Inst. of Semiconductors, CAS |
Pei, Weihua | Inst. of Semiconductors, CAS |
Wang, Yijun | Inst. of Semiconductors, Chinese Acad. of Sciences |
Liu, Zhiduo | Inst. of Semiconductors, Chinese Acad. of Sciences |
Chen, hongda | Inst. of Semiconductors, CAS |
Keywords: Bio-electric sensors - Sensor systems, New sensing techniques, Wearable sensor systems - User centered design and applications
Abstract: In a 256-channel electrode cap for electroencephalogram (EEG) acquisition, the inter-space between adjacent electrodes is around 20mm. Theoretical and experimental evidence predict that improving the density of electrode can get more information from the added electrodes. 10mm or less center distance, corresponding to 1000 electrodes on a full head EEG cap, might be a more proper density to current EEG analysis methods. To develop high-density electrode array with center distance equal or less than 10mm, one must make sure that the adjacent electrodes are electrical isolated. It is difficult to avoid short circuit when common wet electrodes are used to build high-density electrode array. The contact area (about 28mm2 with diameter of 6mm) and gelling method make short circuit easily happen. To provide more isolation space between adjacent electrodes, the contact area of the proposed electrode should be less than 8mm2. To restrict the diffusion of the electrolyte, a customized hydrogel is used to replace the conventional gel. Compared with common wet electrode and gel, preliminary tests indicate that the high-density hydrogel-Ag/AgCl electrodes perform well at the impedance, isolation, as well as data quality in EEG acquisition.
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14:45-15:00, Paper ThCT4.6 | |
A Multichannel EEG Acquisition System with Novel Ag NWs/PDMS Flexible Dry Electrodes |
Wang, Zeyu | Fudan Univ |
chen, chen | Pierre and Marie Curie Univ |
Li, Wei | Fudan Univ |
Yuan, Wei | Printable Electronics Res. Centre, Suzhou Inst. of Nanot |
Han, Tongmeng | Fudan Univ |
Sun, Chenglu | Fudan Univ |
tao, linkai | Eindhoven Univ. of Tech |
Zhao, Yuting | Fudan Univ |
Chen, Wei | Fudan Univ |
Keywords: Bio-electric sensors - Sensor systems, Portable miniaturized systems, Sensor systems and Instrumentation
Abstract: In this paper, a multichannel reconfigurable EEG acquisition system with novel flexible dry electrodes is proposed. The novel electrode is designed to overcome the limitations of conventional wet electrodes such as skin irritation, skin preparation, and conductive gel requirements. It is based on the conductive and stretchable Ag NWs/PDMS composite material and produced by 3D printing technology. Meanwhile, a portable reconfigurable 8-channel EEG acquisition system based on the analog front end ADS1299 is proposed to overcome the drawbacks of traditional EEG acquisition system such as, large in size, difficult to configure, and complicated to use. It can be reconfigured by adjusting the gain of system and sampling rate. To verify the performance of proposed electrodes, a comprehensive test including electrode characterization and signal quality measurement is performed in comparison with Ag/AgCl electrode and Gold Cup electrode. Experiments reveal that proposed electrode achieves favorably results with wet electrodes. Furthermore, the proposed EEG acquisition system with novel dry electrodes is evaluated and compared with the commercial product. The evoked EEG signals (the steady-state visual evoked potentials, SSVEP) acquisition tasks of the proposed system are also conducted. Experimental results exhibit that proposed system satisfies the requirements of multi-channel EEG acquisition and provides a portable and comfortable way for EEG acquisition. With the high-quality sensing ability of the novel electrodes and the programmable gain amplifier of the proposed system, it can be expected to acquire the physiological signals like the electrocardiogram (ECG) and electromyogram (EMG) in the future.
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ThCT5 |
Meeting Room 316A |
Bioinformatics - High Throughput –omic (genomics, Proteomics, Metabolomics,
Lipidomics, and Metagenomics) Data Analytics for Precision Health
(Theme 10) |
Oral Session |
Chair: Quintero Montoya, Olga Lucia | Univ. EAFIT |
Co-Chair: Marcia, Roummel | Univ. of California, Merced |
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13:30-13:45, Paper ThCT5.1 | |
Datalog Extensions for Bioinformatic Data Analysis |
Seo, Jiwon | UNIST |
Keywords: Bioinformatics - Bioinformatics databases
Abstract: Recent growth in public bioinformatic databases has facilitated the analysis of genomic and proteomic data. However, the large size of the datasets makes it hard for non-expert programmers to perform the analysis. In this paper, we present B-Log, a high-level query language for bioinformatic data analysis. Based on Datalog, B-Log can simply express graph analysis algorithms; it is extended with nested tables, recursive aggregations, and foreign functions, which helps quick exploratory analyses. We implemented several analysis algorithms in B-Log; we also implemented a prototype system to explore TCGA dataset. We find B-Log to be useful for exploratory analysis and quick prototyping.
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13:45-14:00, Paper ThCT5.2 | |
Assessing the Predictive Value of Regulatory Molecules for Patient Outcome in Pancreatic Cancer: A Computational Approach |
Kourou, Konstantina | Unit of Biological Applications and Tech. Univ. of Io |
Papaloukas, Costas | Univ. of Ioannina |
Mitsis, Michael | Dept. of Medicine, School of Health Sciences, Univ. of Ioan |
Fotiadis, Dimitrios I. | Univ. of Ioannina |
Keywords: Bioinformatics - Gene regulation, annotation of genes, General and theoretical informatics - Machine learning, Health Informatics - Information technologies for healthcare delivery and management
Abstract: Pancreatic Cancer (PC) can be characterized as one of the most lethal cancers considering its poor diagnosis and symptoms in early stages. To assess the predictive value of regulatory molecules in terms of differentially expressed genes, we first performed a thorough search of gene expression profiling studies in pancreatic cohorts. We obtained the genes that have been identified and validated experimentally to be associated with patient outcome and also differentially expressed in tumors compared with adjacent non-tumor tissues. A two-step upstream analysis on the derived set of the genes under study was performed. The subsequent promoter and pathway analysis unveiled candidate transcription factors and regulatory molecules that potentially have regulated the detected differentially expressed genes. Predictive analysis was applied in the identified regulators and classification algorithms were implemented to model accurately patient outcome. In view of our findings, Gaussian Naïve Bayes model exhibited the highest classification accuracy and f-score concerning the predictive value of regulatory molecules in PC (accuracy= 0.85, f-score = 0.84).
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14:00-14:15, Paper ThCT5.3 | |
Structural Variant Prediction in Extended Pedigrees through Sparse Negative Binomial Genome Signal Recovery |
Banuelos, Mario | Univ. of California, Merced |
Sindi, Suzanne | Univ. of California, Merced |
Marcia, Roummel | Univ. of California, Merced |
Keywords: Bioinformatics - High throughput –omic (genomics, proteomics, metabolomics, lipidomics, and metagenomics) data analytics for precision health, General and theoretical informatics - Supervised learning method
Abstract: Structural variants (SVs) are rearrangements, such as deletions, insertions, duplications, inversions, and translocations, in an individual's genome relative to a reference. SV detection is often marred by high false positive rates due to errors in sequencing and mapping. In previous work, we proposed a maximum likelihood approach to SV prediction that incorporated low-coverage sequencing data and coverage distribution. In particular, we developed a negative binomial framework to reflect a more realistic representation DNA fragment distributions sampled from an individual's genome. In this paper, we leverage relationships between an offspring and both parents, in addition to the negative binomial framework, to improve SV identification accuracy. We present numerical results on both simulated genomes as well as two sequenced parent-child trios from the 1000 Genomes Project.
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14:15-14:30, Paper ThCT5.4 | |
Unsupervised Fuzzy Binning of Metagenomic Sequence Fragments on Three-Dimensional Barnes-Hut T-Stochastic Neighbor Embeddings |
Ariza-Jiménez, Leandro | Univ. EAFIT |
Quintero Montoya, Olga Lucia | Univ. EAFIT |
Pinel, Nicolás | Univ. EAFIT |
Keywords: Bioinformatics - Computational and statistical analysis of metagenomics, Bioinformatics - Sequencing alignment, assembly, and analysis, Bioinformatics - High throughput –omic data visualization
Abstract: Shotgun metagenomic studies attempt to reconstruct population genome sequences from complex microbial communities. In some traditional genome demarcation approaches, high-dimensional sequence data are embedded into two-dimensional spaces and subsequently binned into candidate genomic populations. One such approach uses a combination of the Barnes-Hut approximation and the t-Stochastic Neighbor Embedding (BH-SNE) algorithm for dimensionality reduction of DNA sequence data pentamer profiles; and demarcation of groups based on Gaussian mixture models within human-imposed boundaries. We found that genome demarcation from three-dimensional BH-SNE embeddings consistently results in more accurate binnings than 2-D embeddings. We further addressed the lack of a priori population number information by developing an unsupervised binning approach based on the Subtractive and Fuzzy c-means (FCM) clustering algorithms combined with internal clustering validity indices. Lastly, we addressed the subject of shared membership of individual data objects in a mixed community by assigning a degree of membership to individual objects using the FCM algorithm, and discriminated between confidently binned and uncertain sequence data objects from the community for subsequent biological interpretation. The binning of metagenome sequence fragments according to thresholds in the degree of membership opens the door for the identification of horizontally transferred elements and other genomic regions of uncertain assignment in which biologically meaningful information resides. The reported approach improves the unsupervised genome demarcation of populations within complex communities, increases the confidence in the coherence of the binned elements, and enables the identification of evolutionary processes ignored in hard-binning approaches in shotgun metagenomic studies.
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14:30-14:45, Paper ThCT5.5 | |
Identifi Cation of Primary and Metastatic Melanoma Based on Copy Number Variation |
Seo, Hyein | Korea Advanced Inst. of Science and Tech. (KAIST) |
Cho, Dong-Ho | Korea Advanced Inst. of Science and Tech. (KAIST) |
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14:45-15:00, Paper ThCT5.6 | |
Micro-Inversions in Human Cancer Genomes |
Qu, Li | Peking Univ. Univ |
Zhu, Huaiqiu | Peking Univ |
Wang, May D. | Georgia Tech. and Emory Univ |
Keywords: Bioinformatics - Cancer genomics, Neuro genomics, Cardio genomics, Bioinformatics - High throughput –omic (genomics, proteomics, metabolomics, lipidomics, and metagenomics) data analytics for precision health
Abstract: During the past few years, although scientists and researchers have studied variations in the cancer genomes, our current knowledge about the function of Micro-inversions (MIs) in cancer are still limited. MIs are generally defined as small inversions in DNA segments shorter than 100 bp. To expand our knowledge of their roles in cancer, we analyzed the MIs of 209 samples from four types of cancer, including hepatocellular carcinoma, lung cancer, pancreatic cancer, and bladder cancer. Within all the 209 samples, we identified 2,925 MIs, of which 1,519 (51.93%) are in gene regions. Of the 1,519 MIs in the gene regions, 106 (6.98%) are in the exon regions. We also analyzed 209 healthy samples as the control samples. We further analyzed the distribution of MIs in the four types of cancer among 24 chromosomes. Besides the chromosome preference, different cancer also have different preference for various genes. The MIs preference for various genes among four types of cancer may provide a guidance for the treatment and diagnosis on the four types of cancer. Medical doctors should concentrate more on chromosomes and the genes that MIs prefer to locate on. We also calculated the average count of MIs per individual among each cancer. From this result, we found that the bladder cancer has the most average count of MIs per individual, which means MIs may be more likely to exist in bladder cancer. According to our analysis, MIs play an important role in cancer and should be considered for further analysis.
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ThCT6 |
Meeting Room 316B |
Aneurysma (Theme 5) |
Oral Session |
Chair: Heldt, Thomas | Massachusetts Inst. of Tech |
Co-Chair: Berg, Philipp | Univ. of Magdeburg |
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13:30-13:45, Paper ThCT6.1 | |
3DRA Reconstruction of Intracranial Aneurysms - How Does Voxel Size Influences Morphologic and Hemodynamic Parameters |
Berg, Philipp | Univ. of Magdeburg |
Radtke, Livia | Univ. of Magdeburg |
Voß, Samuel | Univ. of Magdeburg |
Serowy, Steffen | Univ. Hospital Magdeburg |
Janiga, Gabor | Univ. of Magdeburg |
Preim, Bernhard | Univ. of Magdeburg |
Beuing, Oliver | Univ. Hospital Magdeburg |
Saalfeld, Sylvia | Univ. of Magdeburg |
Keywords: Vascular mechanics and hemodynamics - Vascular Hemodynamics, Cardiovascular and respiratory system modeling - Vascular mechanics and hemodynamics
Abstract: Three-dimensional shape analysis and image-based hemodynamic simulations are widely used to assess the individual rupture risk of intracranial aneurysms. However, the quality of those results highly depends on pre-simulative working steps including image reconstruction and segmentation. Within this study, three patient-specific aneurysms were reconstructed using three different voxel sizes (0.1 mm, 0.3 mm, 0.5 mm). Afterwards, 3D segmentations and time-dependent blood flow simulations were carried out to evaluate the impact of the reconstruction size. The results indicate that overall all voxel sizes lead to a qualitatively good agreement with respect to the aneurysm surfaces. However, deviations occur regarding the neck representation as well as the consideration of perforating arteries. Further, morphological differences lead to clear hemodynamic variations, especially for shear force predictions. The findings indicate that depending on the desired analysis, careful reconstruction parameter selection is required. Particularly, for quantitative morphology and blood flow studies, the early step of reconstruction can have a crucial effect on subsequent results.
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13:45-14:00, Paper ThCT6.2 | |
Blood Flow Analysis in Coil Embolized Aneurysms: Difference between Porous Media and Real Coil Geometry Model |
Fujimura, Soichiro | Tokyo Univ. of Science |
Takao, Hiroyuki | Jikei Univ. School of Medicine |
Suzuki, Takashi | Tokyo Univ. of Science |
Uchiyama, Yuya | Tokyo Univ. of Science |
Tanaka, Kazutoshi | Tokyo Univ. of Science |
Otani, Katharina | Siemens Healthcare K.K |
Ishibashi, Toshihiro | The Jikei Univ. School of Medicine, Department of Neurosurg |
Fukudome, Koji | Tokyo Univ. of Science, |
Mamori, Hiroya | Tokyo Univ. of Science |
Yamamoto, Makoto | Tokyo Univ. of Science |
Murayama, Yuichi | Jikei Univ. School of Medicine |
Keywords: Vascular mechanics and hemodynamics - Vascular Disease, Vascular mechanics and hemodynamics - Vascular Hemodynamics
Abstract: Introduction — To clarify the mechanism of aneurysmal recanalization, it is necessary to identify the blood flow characteristics in coil embolized aneurysms. In the studies using computational fluid dynamics (CFD), two options have been mainly used to solve the problem; modeling the coils as porous media or modeling real coil geometries (e.g., using finite element method (FEM) based structural analysis). In this study, we compared the pressure drop between the two coil modeling methods, porous media coil model and real coil geometry model. Materials and Methods— A basic aneurysm model was generated with a dome diameter of 6 mm and neck diameter of 4 mm. Porous coil model was described by Darcy’s law and Ergun’s equation. On the other hand, real coil geometry was generated using FEM based structural analysis. We compared pressure drops passing through the coiled region in CFD with changing the inlet velocity every 0.1 m/s from 0.1 m/s to 1.0 m/s. Results— Comparing the pressure drop in the same VER between porous media and real coil geometry modeling, the values were larger in porous modeling in all the combinations. This result indicate that the porous media model may produce larger pressure drop. In addition, the pressure drop value was also changed due to coil length in the real coil geometry model though the VER values were the same. This result may be obtained from the difference of coil distribution in the aneurysm (i.e., in case of the most pressure dropped case, more coils were distributed at the main flow region). Conclusions— There are clear difference between porous media and real coil geometry model (i.e., porous model using Ergun’s equation may produce larger pressure drop than real coil geometry model). Coil distribution will also affect the flow reduction in aneurysms.
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14:00-14:15, Paper ThCT6.3 | |
Comparison of Hemodynamic Parameters That Can Predict an Aneurysmal Rupture: 20 Patient-Specific Models Experiment |
Fujita, Ryosuke | Tokyo Univ. of Science |
Kawakami, Takumi | Tokyo Univ. of Science |
Ichikawa, Chihiro | Tokyo Univ. of Science |
Yamamoto, Ken | Tokyo Univ. of Science |
Takao, Hiroyuki | Jikei Univ. School of Medicine |
Murayama, Yuichi | Jikei Univ. School of Medicine |
Motosuke, Masahiro | Tokyo Univ. of Science |
Keywords: Vascular mechanics and hemodynamics - Vascular Hemodynamics, Cardiovascular and respiratory system modeling - Vascular mechanics and hemodynamics, Vascular mechanics and hemodynamics - Vascular Disease
Abstract: Hemodynamic analysis of cerebral aneurysms is widely performed to understand the mechanism of aneurysmal rupture. Computational fluid dynamics (CFD) studies have suggested that several hemodynamic parameters are associated with such ruptures. However, a number of factors remain to be addressed to correlate these parameters with aneurysmal ruptures, especially under analytical conditions. Specifically, CFD analysis is often performed with rigid wall models due to computational cost limitations. Here, to evaluate the effects of the deformation of the aneurysmal wall, experimental flow measurement with elastic models under pulsating conditions was conducted using three-dimensional particle image velocimetry (3D PIV). By analyzing 20 patient-specific, elastic, silicone aneurysm models, the hemodynamic parameters of ruptured and unruptured aneurysms were statistically compared to identify the variables that can effectively predict an aneurysmal rupture. Our analyses yielded three parameters (average wall shear stress ratio, in-phase deviation ratio, and pressure difference) which could effectively predict an aneurysmal rupture. These results suggested that measurement of wall shear stress (WSS) at both the aneurysm dome and parent artery is important and that pressure difference can also be a potential indicator of aneurysmal rupture.
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14:15-14:30, Paper ThCT6.4 | |
Multivariate Analysis for Predicting Internal Carotid (IC) and Middle Cerebral (MC) Aneurysmal Rupture by Hemodynamic Parameters |
Suzuki, Takashi | Tokyo Univ. of Science |
Takao, Hiroyuki | Jikei Univ. School of Medicine |
Fujimura, Soichiro | Tokyo Univ. of Science |
Otani, Katharina | Siemens Healthcare K.K |
Uchiyama, Yuya | Tokyo Univ. of Science |
Tanaka, Kazutoshi | Tokyo Univ. of Science |
Ishibashi, Toshihiro | The Jikei Univ. School of Medicine, Department of Neurosurg |
Mamori, Hiroya | Tokyo Univ. of Science |
Murayama, Yuichi | Jikei Univ. School of Medicine |
Yamamoto, Makoto | Tokyo Univ. of Science |
Keywords: Vascular mechanics and hemodynamics - Vascular Hemodynamics, Vascular mechanics and hemodynamics - Vascular Disease
Abstract: Since aneurysmal rupture can hardly be predicted, an objective and precise indicator has been required. Hemodynamic parameters obtained from medical images have been proposed for the rupture prediction indicator (RPI) of cerebral aneurysms in several publications. However, most of those studies were performed using geometries after rupture for ruptured cases, although morphological change of the aneurysm after rupture has been reported. Therefore, the RPI should be investigated with images before rupture. The objective of this study is to find a RPI based on hemodynamic parameters before rupture focusing on IC and MC aneurysms.
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14:30-14:45, Paper ThCT6.5 | |
Hemodynamic Change in a Cerebral Aneurysm Treated by Double Stenting Technique |
Uchiyama, Yuya | Tokyo Univ. of Science |
Takao, Hiroyuki | Jikei Univ. School of Medicine |
Suzuki, Takashi | Tokyo Univ. of Science |
Fujimura, Soichiro | Tokyo Univ. of Science |
Tanaka, Kazutoshi | Tokyo Univ. of Science |
Otani, Katharina | Siemens Healthcare K.K |
Hayakawa, Motoharu | Fujita Health Univ |
Ishibashi, Toshihiro | The Jikei Univ. School of Medicine, Department of Neurosurg |
Fukudome, Koji | Tokyo Univ. of Science, |
Mamori, Hiroya | 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
Abstract: Rupture of a cerebral aneurysm causes subarachnoid hemorrhage which has high fatality rate or possibility of severe disabilities. Larger aneurysms are believed to be more likely to rupture, therefore those aneurysms should be treated by surgical methods. Endovascular treatment such as coil embolization is executed to treat them. Recently, flow diverter (FD) are widely used to treat large or wide neck aneurysms. However, it can be difficult to treat them by single FD deployment because of its insufficient flow disturbance. Therefore, double stenting method sometimes are selected to improve the effect of its blood velocity reduction. In this study, we investigated the hemodynamic changes in an aneurysm with deploying virtual FDs by computational fluid dynamics (CFD). We performed blood flow simulation on no FD deployed, one FD deployed and two FDs deployed cases. The result showed that flow field characters were little changed when a single FD deployed, however, it was greatly changed when two FDs were deployed. Velocity reduction rate values to the no FD deployed case were calculated both FD deployed cases. The velocity reduction in aneurysm sac became greater when two FDs were deployed. Maximum value of aneurysmal velocity reduction rate was 31.0% in one FD deployed case. On the other hand, in two FDs deployed case, the value was 92.8%. Whole the aneurysm sac, velocity reduction rate of two FDs deployed case showed higher velocity reduction rate than the one FD deployed case. In addition, there was flow stagnant region in two FDs deployed case while it did not exist in one FD deployed case. This study showed that double stenting technique certainly has positive effect to hemodynamic in aneurysm which is difficult to treat with only one FD.
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14:45-15:00, Paper ThCT6.6 | |
Relationship between Cerebral Aneurysm Initiation and Hemodynamic Parameters |
Tanaka, Kazutoshi | Tokyo Univ. of Science |
Takao, Hiroyuki | Jikei Univ. School of Medicine |
Suzuki, Takashi | Tokyo Univ. of Science |
Fujimura, Soichiro | Tokyo Univ. of Science |
Uchiyama, Yuya | Tokyo Univ. of Science |
Otani, Katharina | Siemens Healthcare K.K |
Ishibashi, Toshihiro | The Jikei Univ. School of Medicine, Department of Neurosurg |
Mamori, Hiroya | Tokyo Univ. of Science |
Fukudome, Koji | Tokyo Univ. of Science, |
Yamamoto, Makoto | Tokyo Univ. of Science |
Murayama, Yuichi | Jikei Univ. School of Medicine |
Keywords: Vascular mechanics and hemodynamics - Vascular mechanics, Vascular mechanics and hemodynamics - Vascular Hemodynamics
Abstract: Although some research on the relationship between cerebral aneurysm initiation and hemodynamic parameters have been conducted, their mechanisms are not elucidated sufficiently. If the initiation factors were identified, it would be possible to predict the initiation of aneurysms. The purpose of the present study is to investigate the relationship between cerebral aneurysm initiation and hemodynamic factors. Three patients’ blood flow simulations were performed using computational fluid dynamics (CFD) based on the cerebral blood vessel geometry before aneurysm initiation. We evaluated pressure, wall shear stress (WSS), wall shear stress gradient (WSSG), oscillatory shear index (OSI) and gradient oscillatory number (GON) since the previous studies reported their relations to aneurysmal initiation. Additionally, we also focused on the wall shear stress divergence (WSSD) to consider the direction of WSS. Our results indicated that, in all cases, only high WSSD regions corresponded to the initiation regions, and the value of WSSD was remarkably high. Stretching force to the vessel wall may be related to the initiation of cerebral aneurysms.
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ThCT7 |
Meeting Room 316C |
MRI: RF, Parallel Imaging and Pulse Sequence (Theme 2) |
Oral Session |
Chair: Schwartz, Martin | Univ. of Tübingen |
Co-Chair: Wright, Steven M. | Texas A&M Univ |
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13:30-13:45, Paper ThCT7.1 | |
Super Slice Interpolation for Generating Thin-Slice Images from Multichannel Multislice MRI Data |
Feng, Yanqiu | Southern Medical Univ |
Lyu, Mengye | Hong Kong Univ |
Yilong, Liu | The Univ. of Hong Kong |
Victor B., Xie | The Univ. of Hong Kong |
Ka-Fung Henry, Mak | The Univ. of Hong Kong |
Guo, Hua | Tsinghua Univ |
Wu, Ed X. | The Univ. of Hong Kong |
Keywords: Regularized image Reconstruction, Magnetic resonance imaging - Parallel MRI, Magnetic resonance imaging - Other organs
Abstract: Abstract—This study aims to develop a super slice interpolation (SSI) method that generates thin-slice images from multichannel multislice images by exploiting the intra-slice coil sensitivity variations. SSI first calculates the thin-slice sensitivity maps by through-plane interpolation of the sensitivity maps computed from the acquired multislice images. It then reconstructs multiple thin-slice images from each acquired image using a through-plane regularized sensitivity encoding (SENSE) like procedure that consists of an initial SENSE reconstruction and denoising to set the prior information image, and subsequent regularized SENSE reconstruction. We evaluated SSI using multislice brain and abdominal images with typical slice thickness. SSI successfully separated each acquired image into two thinner ones without magnitude bias. Compared with the original thick-slice images, SSI revealed more anatomical details that were consistent with those in the separately acquired thin-slice images. SSI presents a novel slice interpolation approach to obtain thin-slice images from the multichannel thick-slice images.
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13:45-14:00, Paper ThCT7.2 | |
A Surface Electromyography-Driven Magnetic Resonance Sequence Controller for Real-Time Myoelectric Triggered Imaging |
Schwartz, Martin | Univ. of Tübingen |
Martirosian, Petros | Department of Diagnostic and Interventional Radiology, Univ |
Yang, Bin | Inst. of Signal Processing and System Theory, Univ. Of |
Schick, Fritz | Department of Diagnostic and Interventional Radiology, Univ |
Keywords: Magnetic resonance imaging - Other organs, Magnetic resonance imaging - Pulse sequence, Novel imaging modalities
Abstract: Combination of surface electromyography (EMG) with diffusion-weighted magnetic resonance imaging (DW-MRI) enables improved studies of spontaneous mechanical contractions in resting human musculature (SMAM). Mechanical muscular activities follow characteristic electrical neuromuscular activities after a delay of several tens of milliseconds. A low-cost standalone system for simultaneous surface EMG measurements during DW-MRI with a real-time model-based surface EMG activity detection is demonstrated which controls the MR sequence. Therefore, a multilayer perceptron (MLP) with sequential forward selection (SFS) was investigated. MLP achieved an area under curve (AUC) of 0.933 in the detection of small surface EMG activities based on five time-domain features. Integration on a microcontroller system enabled fast real-time surface EMG activity detection with highly flexible trigger time settings. Small deviations with only 7.2±1.7 ms time delay between decision of MLP activity detection and onset of MR sequence were measured.
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14:00-14:15, Paper ThCT7.3 | |
Effect of Incident Field Magnitude and Phase Distribution on RF-Induced Heating Due to Hip Implants |
Kozlov, Mikhail | Max Planck Inst. for Human Cognitive and Brain Sciences |
Horner, Marc | ANSYS, Inc |
Kainz, Wolfgang | Food and Drug Administration |
Angelone, Leonardo M. | US Food and Drug Administration, Center for Devices and Radiolog |
Keywords: Magnetic resonance imaging - Other organs, Magnetic resonance imaging - MRI RF coil technology
Abstract: We investigated how the distribution of magnitude and phase of incident electric field affects RF-induced heating near a hip implant. The results showed that varying the incident electric field, for example due to different phantom shape or different landmark position, for two- or three-dimensional implants can result in up to 50% variation of estimated RF-induced temperature rise. To avoid systematic errors in predicting the RF-induced heating, varied distributions of the incident electric field should be applied.
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14:15-14:30, Paper ThCT7.4 | |
Double-Tuned Cable Traps for Multinuclear MRI and MRS |
Wilcox, Matthew | Texas A&M Univ |
McDougall, Mary | Texas A&M Univ |
Keywords: Magnetic resonance imaging - MRI RF coil technology, Magnetic resonance imaging - MR spectroscopy
Abstract: Using the method of pole-insertion, double-tuned cable traps were constructed and studied. The effectiveness of the method was examined for four different magnetic field strengths. The double-tuned cable trap design was able to effectively block shield currents at two frequencies simultaneously for all field strengths attempted. The effectiveness of the design seemed to increase at higher field strengths, eventually outperforming even the single-tuned cable traps at the highest frequencies examined. The double-tuning method demonstrated here could be a useful cable trap design for multinuclear studies and is considerably more space-efficient than using two single-tuned cable traps mounted in series. This design should be particularly useful in cases where space is limited, such as when using high channel-count array coils.
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14:30-14:45, Paper ThCT7.5 | |
Flexible RF Filtering Front-End for Simultaneous Multinuclear MR Spectroscopy |
Huang, Chung-Huan | Texas A&M Univ |
Ogier, Stephen | Texas A&M Univ |
Gu, Minyu | Texas A&M Univ |
Wright, Steven M. | Texas A&M Univ |
Keywords: Magnetic resonance imaging - MR spectroscopy
Abstract: Simultaneously interrogating multiple nuclei has been of interest since the very earliest days of MRI. Our group and several others are revisiting this topic. Very fast broadband electronics make it possible to digitize a wide spectrum, including multiple nuclei, but this places great demands on data throughput. Another issue is that there can be great variance between RF preamplifier gain required for the different nuclei. To overcome the data problem, it is desirable to use undersampling, but this requires passband filtering around the resonant frequency of each nuclei. Here we present a frequency agile front end that provides separate data paths for each nucleus, either from a single coil or from multiple ports, allows independent gain, filters each using very flexible transmission line filtering, and then combines them back for undersampling. Here we compare the data handling saving by undersampling and the SNR of undersampled vs. fully sampled, and compare this approach to other approaches available to researchers using “off-the-shelf” hardware.
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14:45-15:00, Paper ThCT7.6 | |
4D Dual-Venc Spiral Flow |
Callahan, Sean | Univ. of Louisville |
Henn, Alexander | Univ. of Louisville |
Kendrick, Michael | Veteran's Affairs Medical Center |
Wang, Hui | Philips Medical Systems |
Negahdar, MJ | Univ. of Louisville |
Kheradvar, Arash | Univ. of California, Irvine |
Stoddard, Marcus | Univ. of Louisville |
Amini, Amir | Univ. of Louisville |
Keywords: Magnetic resonance imaging - Pulse sequence, Magnetic resonance imaging - Cardiac imaging
Abstract: Dual-Venc flow acquisition sequences perform flow imaging with differing Vencs. The technique can be used to improve velocity to noise ratio and image quality for diastolic flow velocities as part of a single scan. In this paper, Dual-Venc was used in conjunction with spiral read-out trajectories, offering a faster coverage of k-space. The results illustrate that 4D Dual Venc Spiral Flow behaves similarly to 4D Dual-Venc Cartesian Flow but with the benefit of faster acquisition time and lower echo time (TE).
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ThCT8 |
Meeting Room 318A |
Brain Physiology and Modelling (Theme 6) |
Oral Session |
Chair: Butera, Robert | Georgia Inst. of Tech |
Co-Chair: Zouridakis, George | Univ. of Houston |
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13:30-13:45, Paper ThCT8.1 | |
Auditory Steady-State Responses across Chirp Repetition Rates for Ear-EEG and Scalp EEG |
Christensen, Christian Bech | Aarhus Univ |
Kappel, Simon Lind | Aarhus Univ. Denmark |
Kidmose, Preben | Aarhus Univ. Denmark |
Keywords: Brain physiology and modeling, Brain functional imaging - Evoked potentials, Brain functional imaging - EEG
Abstract: Abstract— Measurement of auditory steady-state responses (ASSR) using ear-EEG potentially enables objective audiometry out of the clinic in the everyday life of hearing aid users. As ear-EEG are measured from electrodes placed within the ear, electrode distances are inherently small and consequently the potential differences, and thereby signal amplitudes, are also small. Because the detection of the ASSR is based on the signal-to-noise ratio (SNR), it is of fundamental interest to know the inherent SNR of the ASSR as a function of the stimulus repetition rate. In this study, ASSRs were recorded using both scalp and ear-EEG in response to broadband chirp stimuli with repetition rates from 20 to 95 Hz. The results showed that in general ear-EEG and scalp EEG SNR was on par across repetition rates; an exception to this was at rates around 40 Hz where the SNR was significantly lower for ear-EEG as compared to scalp EEG. For ear-EEG, the ASSR was relatively constant across repetition rates, whereas the noise showed a 1/f characteristic. In consequence, there was a tendency to increased SNR as a function of repetition rate. This suggests that use of relatively high repetition rates may be beneficial in ear-EEG applications.
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13:45-14:00, Paper ThCT8.2 | |
Graph-Based Models of Cortical Axons for the Prediction of Neuronal Response to Extracellular Electrical Stimulation |
Bingham, Clayton | Univ. of Southern California |
Bouteiller, Jean-Marie Charles | Univ. of Southern California |
Song, Dong | Univ. of Southern California |
Berger, Theodore | Univ. of Southern California |
Keywords: Brain physiology and modeling - Neuron modeling and simulation, Neural stimulation - Deep brain, Brain physiology and modeling - Neural dynamics and computation
Abstract: Over the past decade, many important insights to brain function have been obtained through clever application of detailed compartmental model neurons. New computing capabilities brought opportunities to study large networks of model neurons. Certain applications for these models, such as extracellular electrical stimulation, demand a very high degree of biological realism. While dendrites and somatic morphology may be obtained from explicit reconstructions, this approach is less useful for axonal structures, which are more difficult to characterize across a neuronal population. The purpose of this paper is to extend neuronal morphology generative models to highly branched axon terminal arbors as well as to present a clear use-case for such models in the study of cortical tissue response to externally applied electric fields. The results of this work are (i) presentation and quantitative/qualitative description of generated fibers and (ii) an extracellular electrical stimulation strength-duration study.
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14:00-14:15, Paper ThCT8.3 | |
Decoding Movement States in Stepping Cycles Based on Subthalamic LFPs in Parkinsonian Patients |
Tan, Huiling | Univ. Res. Lecturer in Nuffield Department of Clinical |
Fischer, Petra | Univ. of Oxford |
Shah, Syed Ahmar | Postdoctoral Scientist, Univ. of Oxford |
Vidaurre, Diego | Univ. of Oxford |
Woolrich, Mark | Oxford Univ |
Brown, Peter | Director of the Medical Res. Council Brain Network Dynamics |
Keywords: Brain physiology and modeling, Neural signal processing, Neural stimulation - Deep brain
Abstract: Gait disturbances are a prominent feature of Parkinson’s disease (PD), often refractory to medication or continuous deep brain stimulation (DBS) on basal ganglia targets such as the subthalamic nucleus (STN). Improvement in the treatment of gait disturbances in PD necessitates a better understanding of the neuronal population dynamics associated with gait control in the basal ganglia. Here we sought to identify movement states during stepping, such as left leg stance and right leg stance. To this end we analyzed local field potential (LFP) activity in STN using a combination of the multivariate autoregressive (MAR) model and the Hidden Markov model (HMM). Our results confirm that information is present in the STN related to movement states in stepping cycles, and that it is feasible to decode movement states based on STN LFPs recorded from DBS electrodes. This information can be used to implement temporally flexible stimulation strategies in order to facilitate patterns of neural modulation associated with better gait performance.
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14:15-14:30, Paper ThCT8.4 | |
A Closed-Loop Multi-Channel Asynchronous Neurostimulator to Mimic Neural Code for Cognitive Prosthesis |
Elyahoodayan, Sahar | Univ. of Southern California |
Berger, Theodore | Univ. of Southern California |
Song, Dong | Univ. of Southern California |
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14:30-14:45, Paper ThCT8.5 | |
Sleep Depth Enhancement through Ambient Temperature Manipulation in Mice |
Ajwad, Asmaa | Univ. of Kentucky |
Huffman, Dillon | Univ. of Kentucky |
Yaghouby, Farid | FDA |
O'Hara, Bruce | Univ. of Kentucky |
Sunderam, Sridhar | Univ. of Kentucky |
Keywords: Brain physiology and modeling - Sleep, Neurological disorders - Epilepsy
Abstract: The restorative properties of deep sleep and its central role in learning and memory are well-recognized but still in the process of being elucidated with the help of animal models. Currently available approaches for deep sleep enhancement are mainly pharmacological and may have undesirable side effects on physiology and behavior. Here, we propose a simple strategy for sleep depth enhancement that involves manipulation of ambient temperature (Ta) using a closed-loop control system. Even mild shifts in Ta are known to evoke thermoregulatory responses that alter sleep-wake dynamics. In our experiments, mice evinced greater proportions of deep NREM sleep as well as REM sleep under the dynamic sleep depth modulation protocol compared to a reference baseline in which Ta was left unchanged. The active manipulation approach taken in this study could be used as a more natural means for enhancing deep sleep in patients with disorders like epilepsy, Alzheimer’s disease and Parkinson’s, in which poor quality sleep is common and associated with adverse outcomes.
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14:45-15:00, Paper ThCT8.6 | |
Cholinergic Modulation of CA1 Pyramidal Cells Via M1 Muscarinic Receptor Activation: A Computational Study under Physiological and Hyperactive Levels |
mergenthal, adam | Univ. of Southern California |
Bouteiller, Jean-Marie Charles | Univ. of Southern California |
Berger, Theodore | Univ. of Southern California |
Keywords: Brain physiology and modeling - Neuron modeling and simulation, Brain physiology and modeling - Neural dynamics and computation
Abstract: The hippocampus receives extensive cholinergic modulation from the basal forebrain, which has been shown to have a prominent role in attention, learning, and synaptic plasticity. Disruptions of this modulation have been linked to a variety of neural disorders including Alzheimer's Disease. Pyramidal cells of the CA1 region of the hippocampus express several cholinergic receptor types in different locations throughout the cells' morphology. Developing a computational model of these cells and their modulation provides a unique opportunity to explore how each receptor type alters the overall computational role of the cell. To this end we implemented a kinetic model of the most widely distributed receptor type, the M1 muscarinic receptor and examined its role on excitation of a compartmental model of a CA1 pyramidal cell. We demonstrate that the proposed model replicates the increased pyramidal cell excitability seen in experimental results. We then used the model to replicate the effect of organophosphates, a class of pesticides and chemical weapons, whose effects consist in inhibiting the hydrolysis of acetylcholine; we demonstrated the effect of increasing concentrations of acetylcholine on the pyramidal cell’s excitability. The cell model we implemented and its associated modulation constitute a basis for exploring the effects of cholinergic modulation in a large scale network model of the hippocampus both under physiological and supraphysiological levels.
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ThCT9 |
Meeting Room 318B |
Signal Processing and Classification of Acoustic and Auditory Signals
(Theme 1) |
Oral Session |
Chair: Appakaya, Sai Bharadwaj | Univ. of South Florida |
Co-Chair: Dehak, Najim | Johns Hopkins Univ |
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13:30-13:45, Paper ThCT9.1 | |
Comparison of Cough, Wheeze and Sustained Phonations for Automatic Classification between Healthy Subjects and Asthmatic Patients |
Yadav, Shivani | IISc |
Ghosh, Prasanta | Indian Inst. of Science |
Krishnaswamy, Uma maheswari | M.S.RAMAIAH MEDICAL Coll |
NK, Kausthubha | IISc |
gope, dipanjan | IISc |
Keywords: Signal pattern classification, Neural networks and support vector machines in biosignal processing and classification
Abstract: Abstract— In this work, we consider the task of automatic classification of asthmatic patients and healthy subjects using voice stimuli. Cough and wheeze have been used as voice stimuli for this classification task in the past. In this work, we focus on sustained phonations, namely /A:/, /i:/, /u:/, /eI/, /oU/ and compare their classification performances with the cough and wheeze. Classification experiments using 35 asthmatic patients and 36 healthy subjects show that sustained vowel /i:/ achieves the highest classification accuracy of 80.79% among five vowels considered. However, it is found to be higher and lower than the classification accuracies of 78.72% and 90.25% obtained using cough and wheeze respectively. This suggests that for speech-based asthma classification, /i:/ would be a better choice compared to other vowels considered in this work. However, when non-speech sounds are included for classification, wheeze is a better choice than sustained /i:/.
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13:45-14:00, Paper ThCT9.2 | |
Study of the Automatic Detection of Parkison's Disease Based on Speaker Recognition Technologies and Allophonic Distillation |
Moro Velazquez, Laureano | Johns Hopkins Univ |
Gómez-García, Jorge Andrés | Univ. Nacional De Colombia Sede Manizales |
Godino-Llorente, Juan Ignacio | Univ. Pol. De Madrid |
Rusz, Jan | Czech Tech. Univ. in Prague |
Skodda, Sabine | Univ. Knappschaftskrankenhaus Bochum GmbH |
Grandas-Pérez, Francisco | Hospital General Univ. Gregorio Marañón |
Velázquez, José-Miguel | Hospital General Univ. Gregorio Marañón |
Nöth, Elmar | Univ. of Erlangen-Nuremberg |
Orozco-Arroyave, Juan-Rafael | Univ. De Antioquia |
Dehak, Najim | Johns Hopkins Univ |
Keywords: Signal pattern classification, Time-frequency and time-scale analysis - Time-frequency analysis, Data mining and processing in biosignals
Abstract: The use of new tools to detect Parkinson’s Disease (PD) from speech articulatory movements can have a considerable impact in the diagnosis of patients. In this study, a novel approach involving speaker recognition techniques with allophonic distillation is proposed and tested separately in four parkinsonian speech databases (205 patients and 186 controls in total). This new scheme provides values between 72% and 94% of accuracy in the automatic detection of PD, depending on the database, and improvements up to 9% respect to baseline techniques. Results not only point towards the importance of the segmentation of the speech for the differentiation of parkinsonian and control speakers but confirm previous findings about the relevance of plosives and fricatives in the detection of parkinsonian dysarthria.
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14:00-14:15, Paper ThCT9.3 | |
Learning Front-End Filter-Bank Parameters Using Convolutional Neural Networks for Abnormal Heart Sound Detection |
Humayun, Ahmed Imtiaz | Mhealth Lab, Bangladesh Univ. of Engineering and Tech |
Ghaffarzadegan, Shabnam | Robert Bosch LLC |
Feng, Zhe | Robert Bosch LLC |
Hasan, Taufiq | Bangladesh Univ. of Engineering and Tech |
Keywords: Signal pattern classification, Neural networks and support vector machines in biosignal processing and classification
Abstract: Automatic heart sound abnormality detection can play a vital role in the early diagnosis of heart diseases, particularly in low-resource settings. The state-of-the-art algorithms for this task utilize a set of Finite Impulse Response (FIR) band-pass filters as a front-end followed by a Convolutional Neural Network (CNN) model. In this work, we propound a novel CNN architecture that integrates the front-end band-pass filters within the network using time-convolution (tConv) layers, which enables the FIR filter-bank parameters to become learnable. Different initialization strategies for the learnable filters, including random parameters and a set of predefined FIR filter-bank coefficients, are examined. Using the proposed tConv layers, we add constraints to the learnable FIR filters to ensure linear and zero phase responses. Experimental evaluations are performed on a balanced 4-fold cross-validation task prepared using the PhysioNet/CinC 2016 dataset. Results demonstrate that the proposed models yield superior performance compared to the state-of-the-art system, while the linear phase FIR filter-bank method provides an absolute improvement of 9.54% over the baseline in terms of an overall accuracy metric.
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14:15-14:30, Paper ThCT9.4 | |
Multifractal Analysis of Speech Imagery of IPA Vowels |
Sikdar, Debdeep | IIT Kharagpur |
Roy, Rinku | IIT Kharagpur |
Bakshi, Koushik | Indian Inst. of Tech. Kharagpur |
Mahadevappa, Manjunatha | Indian Inst. of Tech. Kharagpur |
Keywords: Nonlinear dynamic analysis - Biomedical signals, Physiological systems modeling - Multivariate signal processing, Time-frequency and time-scale analysis - Nonstationary processing
Abstract: In Brain Computer Interfacing (BCI), speech imagery is still at nascent stage of development. There are few studies reported considering mostly vowels or monosyllabic words. However, language specific vowels or words made it harder to standardise the whole analysis of electroencephalography (EEG) while distinguishing between them. Through this study, we have explored significance of multifractal parameters for different imagined vowels chosen from International Phonetic Alphabets (IPA). The vowels were categorised into two categories, namely, soft vowels and diphthongs. Multifractal analysis at EEG subband levels were evaluated. We have also reported significant contrasts between spatiotemporal distributions with fractal analysis for activation of different brain regions in imagining vowels.
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14:30-14:45, Paper ThCT9.5 | |
Bruit-Enhancing Phonoangiogram Filter Using Sub-Band Autoregressive Linear Predictive Coding |
Majerus, Steve | APT Center, Cleveland VAMC |
Mandal, Soumyajit | Case Western Res. Univ |
Vince, Geoff | Volcano Corp |
Pinault, Gilles | Case Western Res. Univ |
Damaser, Margot S. | Lerner Res. Inst. the Cleveland Clinic Foundation |
Keywords: Time-frequency and time-scale analysis - Empirical mode decomposition in biosignal analysis, Physiological systems modeling - Signal processing in physiological systems, Parametric filtering and estimation
Abstract: Subjective analysis of bruits has long been an element of vascular access physical exam. Digital recordings of blood flow bruits—phonoangiograms (PAGs)—may provide an objective, non-imaging measure of vascular access stenosis. We have analyzed the long-term stability in PAGs from typical dialysis patients with arteriovenous fistulas and grafts and found that typical patients have correlated PAG spectra. PAGs can be analyzed using nonlinear, sub-band frequency-domain linear prediction to produce both bruit-enhanced recordings and a bruit-enhanced power envelope. This signal processing is novel over prior methods because it adaptively predicts signal envelopes based on physiologic properties of blood flow determined from chronic dialysis recipients. Our results indicate that a generalized bruit-enhancing filter can be developed for dialysis vascular access. Outputs from this filter may be analyzed to determine vascular physiology, including re-stenosis risk.
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14:45-15:00, Paper ThCT9.6 | |
Classification of Parkinson’s Disease Using Pitch Synchronous Speech Analysis |
Appakaya, Sai Bharadwaj | Univ. of South Florida |
Sankar, Ravi | Univ. of South Florida |
Keywords: Nonlinear dynamic analysis - Biomedical signals, Data mining and processing in biosignals, Signal pattern classification
Abstract: Human speech production is a complex task that demands synchronized cognitive and muscular functioning. Assessment of a Parkinson’s disease (PD) patient’s speech using computational methods is a growing field of research. Existing methodologies aim at extraction and usage of features from speech to capture perturbations due to PD. In this paper, we propose a novel methodology for feature extraction and analysis. Features are extracted from each pitch cycle of the speech and variances of the features are used for analysis making this a pitch synchronous methodology. Dimensionality problem is addressed by feature selection, which is followed by an unsupervised k-means clustering to perform classification. A dataset containing 40 participants, 22 (7 female and 15 male) PD and 18 (12 female and 6 male) healthy controls (HC) is used for evaluation. The promising results yielded from this study provides support for our hypothesis that pitch synchronous speech analysis can be useful in PD analysis.
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ThCT10 |
Meeting Room 319A |
Motor Neuroprostheses - II (Theme 6) |
Oral Session |
Chair: Ellis, Michael | Northwestern Univ |
Co-Chair: Petroff, Neil | Tarleton State Univ |
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13:30-13:45, Paper ThCT10.1 | |
Selective Recruitment of Arm Motoneurons in Nonhuman Primates Using Epidural Electrical Stimulation of the Cervical Spinal Cord |
Barra, Beatrice | Univ. of Fribourg |
Roux, Camille | Univ. of Fribourg |
Kaeser, Mélanie | Univ. of Fribourg |
Schiavone, Giuseppe | Ec. Pol. Federale De Lausanne |
Lacour, Stéphanie | EPFL |
Bloch, Jocelyne | Centre Hospitalier Univ. Vaudois, CHUV |
Courtine, Gregoire | EPFL |
Rouiller, Eric M. | Univ. of Fribourg |
Schmidlin, Eric | Univ. of Fribourg |
Capogrosso, Marco | Ec. Pol. Federale De Lausanne |
Keywords: Motor neuroprostheses - Epidural stimulation, Neurorehabilitation, Neuromuscular systems - Peripheral mechanisms
Abstract: Recovery of reaching and grasping ability is the priority for people with cervical spinal cord injury (SCI). Epidural electrical stimulation (EES) has shown promising results in improving motor control after SCI in various animal models and in humans. Notably, the application of stimulation bursts with spatiotemporal sequences that reproduce the natural activation of motoneurons restored skilled leg movements in rodent and nonhuman primate models of SCI. Here, we studied whether this conceptual framework could be transferred to the design of cervical EES protocols for the recovery of reaching and grasping in nonhuman primates. We recorded muscle activity during a reaching and grasping task in a macaque monkey and found that this task involves a stereotypical spatiotemporal map of motoneuron activation. We then characterized the specificity of a spinal implant for the delivery of EES to cervical spinal segments in the same animal. Finally, we combined these results to design a simple stimulation protocol that may reproduce natural motoneuron activation and thus facilitate upper limb movements after injury.
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13:45-14:00, Paper ThCT10.2 | |
Flexibility of Finger Activation Patterns Elicited through Non-Invasive Multi-Electrode Nerve Stimulation |
Shin, Henry | Univ. of North Carolina at Chapel Hill |
Hu, Xiaogang | Univ. of North Carolina-Chapel Hill |
Keywords: Motor neuroprostheses - Neuromuscular stimulation, Neural interfaces - Body interfaces, Neurorehabilitation
Abstract: The inability to effectively activate and control skeletal muscles is a common impairment following a variety of neurological conditions or injuries. One common approach to restoring or augmenting this impairment is the use of external electrical stimulation of the muscles, called functional electrical stimulation (FES). Typically targeted directly at the anatomical muscle belly, existing methodologies often involve high current amplitudes, limited superficial muscle activation, and early onset of muscle fatigue. We have recently explored the capabilities of a non-invasive peripheral nerve stimulation method for the dexterous control of finger and hand muscles. Further development of our stimulation system has enabled us to manually search across a variety of stimulation locations with increased consistency and efficiency. This study examined the preliminary results in two subjects of an automated stimulation system which can rapidly characterize a large combination of stimulation electrodes. Our preliminary findings suggested that the stimulation grid was able to produce a number of clustered EMG activities and finger forces. This robust ability to flexibly generate different grasp patterns demonstrates the promise of the methodology in future applications for FES and rehabilitation.
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14:00-14:15, Paper ThCT10.3 | |
Long-Term Functionality of a Soft Electrode Array for Epidural Spinal Cord Stimulation in a Minipig Model |
Schiavone, Giuseppe | Ec. Pol. Federale De Lausanne |
Wagner, Fabien | EPFL Lausanne |
Fallegger, Florian | EPFL Lausanne |
Kang, Xiao-Yang | EPFL Lausanne |
Vachicouras, Nicolas | EPFL Lausanne |
Barra, Beatrice | Univ. of Fribourg |
Capogrosso, Marco | Ec. Pol. Federale De Lausanne |
Bloch, Jocelyne | Centre Hospitalier Univ. Vaudois, CHUV |
Courtine, Gregoire | EPFL |
Lacour, Stéphanie | EPFL |
Keywords: Motor neuroprostheses - Epidural stimulation, Neural interfaces - Microelectrode technology, Neural interfaces - Tissue-electrode interface
Abstract: Long-term biointegration of man-made neural interfaces is influenced by the mechanical properties of the implant materials. Substantial experimental work currently aims at replacing conventional hard implant materials with soft alternatives that can favour a lower immune response. Here we assess the performance of a soft electrode array implanted in the spinal epidural space of a minipig model for a period of 6 months. The electrode array includes platinum-silicone electrode contacts and elastic thin-film gold interconnects embedded in silicone. In-vivo electrode impedance and voltage transients were monitored over time. Following implantation, epidural stimulation produced muscle-specific evoked potentials and visible muscle contractions. Over time, post-operative and stimulation induced changes in electrode impedance were observed. Such trends provide a basis for future technological improvements aiming at ensuring the stability of soft implantable electrodes for neural interfacing.
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14:15-14:30, Paper ThCT10.4 | |
A Novel EMG-Driven Functional Electrical Stimulator for Post-Stroke Individuals to Practice Activities of Daily Living |
Yao, Jun | Northwestern Univ |
Sullivan, Jane | Northwestern Univ |
Dewald, Julius P. A. | Northwestern Univ |
Keywords: Motor neuroprostheses - Neuromuscular stimulation, Neural interfaces - Body interfaces, Neurorehabilitation
Abstract: Prior research has demonstrated that hand function can be recovered in individuals with mild stroke through an intervention that is both ‘intense’ and ‘functional’. However, in individuals with moderate to severe post stroke hand paresis, current evidence for an effective intervention to regain hand function is almost absent. A possible contributor to such poor recovery in these individuals may be the inability to intensively practice with the paretic hand during activities of daily living (ADLs). Many ADLs require use of the paretic arm and hand. Due to post-stroke abnormal muscle synergies, functional arm movements, such as lifting or reaching, often result in unwanted activity in the wrist/finger flexors. This makes voluntary hand opening more difficult. A possible solution to enable these individuals to practice with their paretic hand in a functional context is using devices to assist hand opening. Unfortunately, most of currently available hand rehabilitation devices do not sufficiently address hand opening with the appearance of abnormal muscle synergies. We, therefore, developed a synergy resistant, electromyographic (EMG)-driven electrical stimulation device that allows for Reliable and Intuitive control of the hand (ReIn-Hand) opening while using the paretic arm during lifting and reaching.
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14:30-14:45, Paper ThCT10.5 | |
Applying Multichannel Optogenetic System for Epidural Spinal Cord Stimulation in Rats |
Chang, Shih-Yin | The Univ. of Tokyo |
Naganuma, Kazunori | The Univ. of Tokyo |
Kanazawa, Hoshinori | The Univ. of Tokyo |
Sekino, Masaki | The Univ. of Tokyo |
Onodera, Hiroshi | Univ. of Tokyo Graduate School of Engineering |
Kuniyoshi, Yasuo | Univ. of Tokyo |
Keywords: Motor neuroprostheses - Epidural stimulation, Neural stimulation, Neural interfaces - Body interfaces
Abstract: This study reports on the technique of applying multichannel optogenetic system to spinal cord stimulation in rats. Epidural spinal cord stimulation has been shown to reactivate spinalized hind limb motion; however, the stimulating parameters and detailed mechanism remain unclear. In order to utilize the high spatial resolution and cell type selectivity of optogenetics for studying the mechanism behind epidural spinal cord stimulation, a multichannel optical fiber bundle was designed, composed of 720 optical fibers of 200 μm diameter arranged in a 48×15 matrix cover the vertebral columns of rats from level T13 to L2. The stimulating location was controlled by changing the direction of projection of a laser diode, and the appropriate projecting angle to obtain the maximum optical power output of each fiber was determined by a hill-climbing algorithm. A spinal cord window was developed to fit the head of the optical fiber bundle onto the dorsal part of rat spinal cord. Preliminary test in a rat revealed different stimulating area distribution of the optogenetically induced tibialis anterior (TA) and medial gastrocnemius (MG) muscle reactions and demonstrated the capability of the system for in-vivo study.
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ThCT11 |
Meeting Room 319B |
Time-Frequency Analysis in Sleep Studies (Theme 1) |
Oral Session |
Chair: Wang, Yiwen | Hong Kong Univ. of Science and Tech |
Co-Chair: Porta, Alberto | Univ. Degli Studi Di Milano |
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13:30-13:45, Paper ThCT11.1 | |
Feature Selection for the Detection of Sleep Apnea Using Multi-Bio Signals from Overnight Polysomnography |
LI, XILIN | Univ. of Tech. Sydney |
Al-Ani, Ahmed | Univ. of Tech. Sydney |
Ling, Sai Ho, Steve | Univ. of Tech. Sydney |
Keywords: Time-frequency and time-scale analysis - Time-frequency analysis, Time-frequency and time-scale analysis - Wavelets, Time-frequency and time-scale analysis - Nonstationary processing
Abstract: Patients with sleep apnea (SA) are at increased risk of stroke and cardiovascular disease. Diagnosis of sleep apnea depends on the standard overnight polysomnography (PSG). In this study, the DREAM Apnea Database was used to evaluate the importance of the various features proposed in the literature for the analysis of sleep apnea. various time- and frequency- domain features that include wavelet and power spectral density were extracted from ECG, EMG, EEG, airflow, SaO2, abdominal and thoracic recordings. Evaluation measures of one-way analysis of variance (ANOVA) and Rank-Sum test were used to test the performance of different features. The selected feature subset indicated that frequency-domain features outperform time-domain ones. This study will help in enhancing the detection accuracy of sleep apnea for the various polysomnography signals.
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13:45-14:00, Paper ThCT11.2 | |
Autonomic Cardiac Activity in Adults with Short and Long Sleep Onset Latency |
Nano, Marina-Marinela | Eindhoven Univ. of Tech |
Fonseca, Pedro | Philips Res. and Eindhoven Univ. of Tech |
Overeem, Sebastiaan | Kempenhaeghe Foundation, Sleep Medicine Centre |
Vullings, Rik | Eindhoven Univ. of Tech |
Aarts, Ronald M. | Philips |
Keywords: Time-frequency and time-scale analysis - Time-frequency analysis, Physiological systems modeling - Signal processing in physiological systems
Abstract: Autonomic cardiac activity during sleep has been widely studied. Research has mostly focused on cardiac activity between different sleep stages and wakefulness as well as between normal and pathological sleep. This work investigates autonomic activity changes during sleep onset in healthy subjects with long and short sleep onset latency (SOL). Polysomnography (PSG) and electrocardiography (ECG) were simultaneously recorded in 186 healthy subjects during a single night. Autonomic activity was assessed based on frequency domain analysis of RR intervals and results show that the analysis of RR intervals differs significantly between the short SOL and the long SOL groups. We found that the spectral power in the low frequency band (LF) was significantly higher in the long SOL group compared to the short SOL group in the first 10 minutes in bed intended to sleep. There was no significant difference for LF and the spectral power in the high frequency band (HF) 10 minutes before and after sleep onset between the two groups. Only in the short SOL group there was a significant increase in HF from the first 10 minutes in bed intended to sleep to 10 minutes before SO, while LF decreased significantly in both groups. The effect of time (5.5-min bin) on the heart rate variability (HRV) features around sleep onset showed that both LF and HF differed significantly during the period surrounding sleep onset only in the short SOL group.
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14:00-14:15, Paper ThCT11.3 | |
Automatic Sleep Stage Classification Using Single-Channel EEG: Learning Sequential Features with Attention-Based Recurrent Neural Networks |
Phan, Huy | Univ. of Oxford |
Andreotti, Fernando | Univ. of Oxford |
Cooray, Navin | Inst. of Biomedical Engineering, Univ. of Oxford |
Chén, Oliver | Univ. of Oxford |
De Vos, Maarten | Univ. of Oxford |
Keywords: Time-frequency and time-scale analysis - Time-frequency analysis, Signal pattern classification, Neural networks and support vector machines in biosignal processing and classification
Abstract: We propose in this work a feature learning approach using deep bidirectional recurrent neural networks (RNNs) with attention mechanism for single-channel automatic sleep stage classification. We firstly decompose an EEG epoch into multiple small frames and subsequently transform them into a sequence of frame-wise feature vectors. Given the training sequences, the attention-based RNN is trained in a sequence-to-label fashion for sleep stage classification. Due to discriminative training, the network is expected to encode information of an input sequence into a high-level feature vector after the attention layer. We, therefore, treat the trained network as a feature extractor and extract these feature vectors for classification which is accomplished by a linear SVM classifier. We also propose a discriminative method to learn a filter bank with a DNN for preprocessing purpose. Filtering the frame-wise feature vectors with the learned filter bank beforehand leads to further improvement on the classification performance. The proposed approach demonstrates good performance on the Sleep-EDF dataset.
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14:15-14:30, Paper ThCT11.4 | |
Characteristics of EEG Power Spectrum During Sleep Spindle Events in ADHD Children |
De Dea, Federica | Univ. of Trieste |
Zanus, Caterina | Child Neuropsychiatry, IRCCS Children’s Hospital “Burlo Garofolo |
Carrozzi, Marco | Child Neuropsychiatry, IRCCS Children’s Hospital “Burlo Garofolo |
Stecca, Matteo | Child Neuropsychiatry, IRCCS Children’s Hospital “Burlo Garofolo |
Accardo, Agostino | Univ. of Trieste |
Keywords: Time-frequency and time-scale analysis - Time-frequency analysis, Nonlinear dynamic analysis - Biomedical signals
Abstract: The attention-deficit/hyperactivity disorder (ADHD) is a common psychiatric disorder that interferes with the typical development and both learning and motor functioning in a child’s life. Most of the children with ADHD present also sleep problems like difficulties in falling asleep and maintaining sleep. Sleep spindles are characteristic waves of sleep stage 2 in humans and are characterized by a fusiform morphology. In the last years, the empirical evidence indicates that spindles are associated with cognitive faculties and intelligence as well as with several disease states. On the other hand, power spectral analysis of EEG represents a powerful noninvasive tool for examining cerebral behavior. The aim of this study is to evaluate the differences between ADHD and healthy children of the power spectral values in delta, theta, alpha, beta and gamma bands, before, during and after sleep spindles. Our results show significant differences concentrated in the period immediately after spindle epochs, in the left hemisphere of the brain, in almost all bands, with greater values in control than in ADHD children.
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14:30-14:45, Paper ThCT11.5 | |
Automating the Detection of REM Sleep Behaviour Disorder |
Cooray, Navin | Inst. of Biomedical Engineering, Univ. of Oxford |
Andreotti, Fernando | Univ. of Oxford |
Lo, Christine | Sheffield Inst. of Translational Neuroscience |
Symmonds, Mkael | Department of Clinical Neurophysiology, Oxford Univ. Hospit |
Hu, Michele | Uffield Department of Clinical Neurosciences, Univ. of Oxfo |
De Vos, Maarten | Univ. of Oxford |
Keywords: Signal pattern classification, Time-frequency and time-scale analysis - Time-frequency analysis
Abstract: This study aims to develop automated diagnostic tools to aid in the identification of rapid-eye-movement (REM) sleep behaviour disorder (RBD). Those diagnosed with RBD enact their dreams and therefore present an abnormal characteristic of movement during REM sleep. Several methods have been proposed for RBD detection that use electromyogram (EMG) recordings and manually annotated sleep stages to objectively quantify abnormal REM movement. In this work we further develop these proven techniques with additional features that incorporate the relationship of muscle movement between sleep stages and general sleep architecture. Performance is evaluated using polysomnography (PSG) recordings from 43 aged-matched healthy controls and subjects diagnosed with RBD obtained from multiple institutions and publicly available resources. Using a random forest classifier with established and additional features, the performance of RBD detection was shown to improve upon established metrics (achieving 88% accuracy, 91% sensitivity, and 86% specificity).
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14:45-15:00, Paper ThCT11.6 | |
Quantitative Analysis of a Marked Point Process Based Sleep Spindle Detector |
Akella, Shailaja | Univ. of Florida, Gainesville |
Principe, Jose | Univ. of Florida |
Keywords: Time-frequency and time-scale analysis - Empirical mode decomposition in biosignal analysis, Nonlinear dynamic analysis - Biomedical signals, Parametric filtering and estimation
Abstract: Sleep spindles result from interactions between the thalamic and cortical neurons in the NREM2 stage. Studies show that these waxing and waning episodes of field potentials may have an implied role in memory consolidation, cellular plasticity and neuronal development besides serving as important markers in several neuronal pathologies. For these reasons, accurate spindle scoring of polysomnographic signals is important and has garnered interest in automating the tedious process of scoring via visual inspection. In this paper, we propose a transient model for automatic sleep spindle detection designed as a Marked Point Process (MPP). Further, in order to simplify the model development, the determination of the atoms was done independently for each of the EEG bands. However, this brings the problem of quantifying the effect of the required bandpass filtering, which was not done in previous work. Here we change the Q of the filters and evaluate the effect on the detections provided by the model, when compared with two sleep experts. Several statistics are utilized, and we conclude that the design of the bandpass filters affects the performance. Low Q filters were thought necessary, but the results show that the best Q - factor is around 2.
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ThCT12 |
Meeting Room 321A |
Joint Biomechanics (Theme 8) |
Oral Session |
Chair: Lee, Sabrina | Northwestern Univ |
Co-Chair: Forner-Cordero, Arturo | Escola Pol. Da Univ. De Sao Paulo |
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13:30-13:45, Paper ThCT12.1 | |
In Vivo Relationship between Joint Stiffness, Joint-Based Estimates of Muscle Stiffness, and Shear-Wave Velocity |
Vigotsky, Andrew | Northwestern Univ |
Rouse, Elliott | Univ. of Michigan |
Lee, Sabrina | Northwestern Univ |
Keywords: Joint biomechanics, Modeling and simulation in musculoskeletal biomechanics, Biomechanics and robotics - Clinical evaluation in rehabilitation and orthopedics
Abstract: Shear-wave (SW) ultrasound elastography is both a clinical and research tool that is increasingly being used to quantify the material properties of muscle. However, how SW velocity relates to stiffness changes on the joint- and muscle-levels is poorly understood. Therefore, the purpose of this work was to develop a biomechanical model to estimate plantar flexor muscle stiffness, and measure joint stiffness, joint-based estimates of muscle stiffness, and medial gatrocnemius (MG) SW velocity under different activations (0, 20, and 40%) to quantify the relationships between 1) joint stiffness and joint-based estimates of muscle stiffness; 2) joint stiffness and MG SW velocity; and 3) joint-based estimates of muscle stiffness and MG SW velocity. Our main findings include strong relationships between 1) joint stiffness and joint-based estimates of muscle stiffness ( R2 = 0.70) and 2) joint stiffness and MG SW velocity ( R2 = 0.66), and a weak relationship between joint-based estimates of muscle stiffness and MG SW velocity ( R2 = 0.24). These findings further our understanding of SW velocity measures in muscle and provide a biomechanical model to decompose muscle stiffness from joint stiffness.
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13:45-14:00, Paper ThCT12.2 | |
Elbow Joint Angle Estimation with Surface Electromyography and Autoregressive Moving Average Models |
Fischi Sommer, Leonardo | Univ. of São Paulo |
Barreira, Cauê | Univ. of Sao Paulo |
López Noriega, Carlos | Univ. of São Paulo |
Camargo-Junior, Franklin | Univ. of São Paulo |
Moura, Rafael Traldi | Pol. School. Univ. of Sao Paulo |
Forner-Cordero, Arturo | Pol. School. Univ. of Sao Paulo |
Keywords: Human machine interfaces and robotics applications, Neural-robotic interfaces, Rehabilitation robotics and biomechanics - Exoskeleton robotics
Abstract: This paper presents a method to estimate the elbow joint angle from surface electromyography (sEMG) measurements of biceps, triceps and brachioradialis. This estimation is of major importance for the design of human robot interfaces based on sEMG. It is also relevant to model the muscular system and to design biomimetic mechanisms. However, the processing and interpretation of electromyographic signals is challenging due to nonlinearities, unmodeled muscle dynamics, noise and interferences. In order to determine an estimation model and a calibration procedure for the model parameters, a set of experiments were carried out with six subjects. The experiments consisted of series of continuous (cyclical) and discrete elbow flexo-extensions with three different loads (i.e. 0 kg, 1.5kg and 3 kg). The sEMG data from the biceps brachii, triceps brachii and brachioradialis and the joint angle were recorded. Four different modeling techniques were evaluated: State Space (SS), Autoregressive with Exogenous Input (ARX), Autoregressive Moving-Average with Exogenous Input (ARMAX), Autoregressive Integrated Moving-Average with Exogenous Input (ARIMAX). After the model was selected, a second experiment was performed in order to validate the estimation procedure. The results show a procedure to estimate the EMG-to-angle relation with high correlation and low mean square-root errors with respect to the measured angle data.
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14:00-14:15, Paper ThCT12.3 | |
A New Algorithm to Estimate Glenohumeral Joint Location Based on Scapula Rhythm |
Heidari, Omid | Idaho State Univ |
Pourgharibshahi, Vahid | Idaho State Univ |
Urfer, Alex | Idaho State Univ |
Perez Gracia, Alba | Idaho State Univ |
Keywords: New technologies and methodologies in human movement analysis, Joint biomechanics, Humanoid robotics
Abstract: This work analyzes the human shoulder complex workspace by introducing a new method to estimate the intra-articulation location of the glenohumeral (GH) joint. The proposed algorithm is based on the hypothesis of the GH joint remaining fixed during the first 30 degrees of shoulder elevation. This part of any vertical movement is considered to estimate the center of spherical motions (CoS) where the humeral head is located. For the experimental results, six subjects performed 5 cycles of 12 different movements in different planes. The data are collected using motion capture, for various landmarks of the shoulder girdle. With the proposed method, estimating the location of GH is possible for any motion of the shoulder girdle complex. In order to complete the kinematic model of the shoulder complex, PCA is used to identify a relation between the shoulder joints. This technique indicates that the shoulder complex can be modeled using two degrees of freedom (DOFs) to locate the spherical GH joint. The overall shoulder model can generate any possible vertical motion of the human shoulder.
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14:15-14:30, Paper ThCT12.4 | |
Shoulder Glenohumeral Elevation Estimation Based on Upper Arm Orientation |
Hamdan, Sara | Ozyegin Univ |
Oztop, Erhan | Ozyegin Univ |
Furukawa, Jun-ichiro | ATR Computational Neuroscience Labs |
Morimoto, Jun | ATR Computational Neuroscience Labs |
Ugurlu, Barkan | Ozyegin Univ |
Keywords: Robotics - Orthotics, Modeling and simulation in biomechanics - Orthotics
Abstract: In this paper, the shoulder glenohumeral displacement during the movement of the upper arm is studied. Four modeling approaches were examined and compared to estimate the humeral head elevation (vertical displacement) and translation (horizontal displacement). A biomechanics-inspired method was used firstly to model the glenohumeral displacement in which a least squares method was implemented for parameter identification. Then, three Gaussian process regression models were used in which the following variable sets were employed: i)shoulder adduction/abduction angle, ii) combination of shoulder adduction/abduction and flexion/extension angles, iii) overall upper arm orientation in the form of quaternions. In order to test the respective performances of these four models, we collected motion capture data and compared the models’ representative capabilities. As a result, Gaussian process regression that considered the overall upper arm orientation outperformed the other modeling approaches; however, it should be noted that the other methods also provided accuracy levels that may be sufficient depending on task requirements.
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14:30-14:45, Paper ThCT12.5 | |
A Functional Method for Generating Individualized Spine Models from Motion-Capture Data |
Seko, Sarah | UC Berkeley |
Matthew, Robert Peter | UC Berkeley |
Bajcsy, Ruzena | UC Berkeley, CITRIS |
Lotz, Jeffrey | Orthopaedic Surgery, Univ. of California at Berkeley |
Keywords: Joint biomechanics, Modeling and simulation in musculoskeletal biomechanics, Optimization in musculoskeletal biomechanics
Abstract: A representative model is necessary for the analysis of spine kinematics and dynamics during motion. Existing models, based on stationary imaging or cadaveric data, may not be accurate through the full range of spinal motion or for clinical populations. In this paper, we propose a functional method for estimating subject-specific spinal joint centers, generating a one-joint or two-joint kinematic model of the spine. These models are driven by the motion of the thorax and pelvis as observed by eight surface landmarks. We apply this method to experimental data from ten subjects performing flexion/extension and sit-to-stand motions. The recovered functional models are assessed against an allometric model though the analysis of marker residuals. We found that the functional models provide lower residuals than the allometric methods. Between the functional models, the two-joint model provided lower residuals with less sensitivity to the training action, while the one-joint model should be trained on the motion of interest.
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14:45-15:00, Paper ThCT12.6 | |
Generalized Lower Limb Joint Angular Phase Space Analysis of Subject Specific Normal and Modified Gait |
Rodrigues, Carlos M. B. | INESCTEC - Tech. & Science Associate Lab |
Correia, Miguel | Univ. Do Porto, Faculdade De Engenharia |
Abrantes, João M. C. S. | MovLab - ULHT |
Rodrigues, Marco Aurélio Benedetti | Federal Univ. of Pernambuco |
Nadal, Jurandir | Federal Univ. of Rio De Janeiro |
Keywords: Joint biomechanics, Mechanics of locomotion and balance, Modeling and simulation in musculoskeletal biomechanics
Abstract: This study presents and applies generalized angular phase space analysis to lower limb joint angles of specific subject during normal and modified gait for discrimination of gait and joint angular movements. Case study of an adult healthy male in-vivo and noninvasive kinematic assessment of skin surface adhesive markers at lower limb was performed at human movement lab during normal gait, stiff knee gait and slow running. Musculoskeletal modeling was performed using AnyGait v.0.92 morphing Twente Lower Extremity Model (TLEM) to match the size and joint morphology of the stick-figure model. Inverse kinematics was performed obtaining hip, knee and ankle joint flexion-extension angular displacements, velocities and accelerations. Generalized phase space analysis was applied to lower limb joint angular displacements, velocities and accelerations. Directional statistics was applied to generalized phase planes with mean direction, resultant length and circular standard deviation assessment. Rayleigh test was employed for directional concentration and coordination assessment, and Watson’s U2 goodness of fit test applied to the von Mises distribution. Results point for the importance of subject specific study, generalized joint angular phase space analysis, comparing results with other normalization methods and validation of applied methods with qualitative clinical analysis.
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ThCT13 |
Meeting Room 321B |
Cardiovascular, Pulmonary, and Sleep Engineering (Theme 5) |
Oral Session |
Chair: Kim, Sung June | Seoul National Univ |
Co-Chair: Harasek, Michael | Vienna Univ. of Tech |
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13:30-13:45, Paper ThCT13.1 | |
A Guide-Wired Helical Microrobot for Mechanical Thrombectomy: A Feasibility Study |
Nguyen, Kim Tien | Chonnam National Univ |
Go, Gwangjun | Robot Res. Initiative |
Choi, Eunpyo | Chonnam National Univ |
Kang, Byungjeon | Robot Res. Initiative, Chonnam National Univ |
Park, Jongoh | Chonnam National Univ |
Kim, Chang-Sei | Chonnam National Univ |
Keywords: Cardiovascular, respiratory, and sleep devices - Therapeutics, Cardiovascular, respiratory, and sleep devices - Smart systems
Abstract: In this paper, we present a novel guide-wired helical microrobot for mechanical thrombectomy in cardio- vascular system, especially for calcified thrombus therapeutics. We designed and fabricated a prototype of the helical shape microrobot equipped with a freely rotatable spherical joint connected to a catheter guidewire, that enables drilling capability to remove calcified objects in vascular. The guidewire helps supporting and maneuvering the microrobot against blood flow during thrombus removal procedure. In addition to the microrobot, an enhanced electromagnetic navigation system (ENS) is implemented to utilize high frequency operation based on resonant effect, which enables powerful drilling force of the microrobot. The in-vitro experimental results illustrate that the suggested method could successfully enhance the locomotion and the drilling force of the helical microrobot that would be sufficient for future mechanical thrombectomy application in cardiovascular therapeutics.
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13:45-14:00, Paper ThCT13.2 | |
Preliminary Study of Palatal Implant for Sleep Apnea Control |
Seo, Jungmin | Seoul National Univ |
Kim, Jeong-Whun | Seoul National Univ. Coll. of Medicine |
Cho, Sung Woo | Department of Otorhinolaryngology, Seoul National Univ. Hos |
Shim, Shinyong | Seoul National Univ |
Choi, Jin-Woo | Louisiana State Univ |
Kim, Sung June | Seoul National Univ |
Keywords: Cardiovascular, respiratory, and sleep devices - Implantables, Sleep - Obstructive sleep apnea, Sleep - Sleep apnea therapy
Abstract: A fully-implantable device for treating obstructive sleep apnea (OSA) is conceptually suggested using soft palate stimulation. In this research, two in vivo studies were conducted to demonstrate electrical and physical feasibilities of the suggested device. First, electrical stimulation was delivered to the soft palate of a rabbit using a stimulator ASIC. The stimulation frequencies were swept from 20 Hz to 200 Hz to find out the appropriate parameter. Also, threshold level of the current pulse was evaluated to be 1.10 mA with an observance of a C-arm fluoroscopy. Second, a mock-up was fabricated with liquid crystal polymer (LCP), reflecting dimensions of the suggested device. The mock-up was inserted toward the soft palate of a rabbit by incising the hard palate in a lateral direction. After the mock-up was inserted, protrusion of the device was not detected and the subject stayed alive for at least a month at the time of this writing. Finally, several discussions on the palatal implant fabrication with LCP are presented.
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14:00-14:15, Paper ThCT13.3 | |
Performance Assessment of a Dedicated Reflectance Pulse Oximeter in a Neonatal Intensive Care Unit |
Proença, Martin | Csem Sa |
Grossenbacher, Olivier | Csem Sa |
Dasen, Stephan | CSEM |
Moser, Virginie | CSEM |
Ostojic, Daniel | Univ. of Zurich |
Lemkaddem, Alia | CSEM |
Ferrario, Damien | CSEM |
Lemay, Mathieu | CSEM |
Wolf, Martin | Univ. of Zurich |
Fauchère, Jean-Claude | Univ. of Zurich |
Karen, Tanja | Univ. of Zurich |
Keywords: Pulmonary and critical care – Multimodality monitoring in intensive care, Pulmonary and critical care - Bioengineering applications in Intensive care
Abstract: The measurement of peripheral oxygen saturation (SpO2) in neonatal intensive care units (NICUs) poses a significant challenge. Motion artifacts due to the patient's limb motion induce many false alarms, which in turn cause an additional workload for the medical staff and anxiety for the parents. We developed a reflectance pulse oximeter dedicated to be placed at the patient's forehead, which is less prone to such artifacts. We trained our algorithms for SpO2 estimation on 8 adult healthy volunteers participating in a controlled desaturation study. We then validated our SpO2 monitoring system on 25 newborn patients monitored in an NICU. We further evaluated the versatility and resilience to low signal-to-noise ratios (SNR) of our solution by testing it on signals acquired in a low-perfusion region (upper right part of the chest) of our adult volunteers. We obtained an SpO2 estimation accuracy (Arms) of 1.9 % and 3.1 % at the forehead and the chest in our adult volunteers, respectively. These performances were obtained after automatic rejection of 0.1 % and 30.0 %, respectively, of low-SNR signals by our dedicated quality index. In the dataset recorded on newborn patients in the NICU, we obtained an accuracy of 3.9 % after automatic rejection of 11.7 % of low-SNR signals by our quality index. These analyses were carried out following the procedures suggested by the ISO 80601-2-61:2011 standard, which specifies a target Arms ≤ 4 % for SpO2 monitoring applications. These promising results suggest that reflectance pulse oximeters can achieve clinically acceptable accuracy, while being placed at locations less sensitive to limb motion artifacts – such as the forehead – thereby reducing the amount of SpO2–related false alarms in NICUs.
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14:15-14:30, Paper ThCT13.4 | |
Basic Performance Tests of the MILL Intravascular CO2 Removal Catheter |
Janeczek, Christoph | Vienna Univ. of Tech |
Lukitsch, Benjamin | Vienna Univ. of Tech |
Huber-Dangl, Florentine | Vienna Univ. of Tech |
Karabegovic, Alen | Vienna Univ. of Tech |
Jordan, Christian | Vienna Univ. of Tech |
Haddadi, Bahram | Vienna Univ. of Tech |
Ullrich, Roman | CCore Tech. GmbH |
Krenn, Claus Georg | CCore Tech. GmbH |
Gfoehler, Margit | TU Wien |
Harasek, Michael | Vienna Univ. of Tech |
Keywords: Pulmonary and critical care - Pulmonary rehabilitation, Cardiovascular, respiratory, and sleep devices - Wearables, Pulmonary and critical care - Pulmonary disease
Abstract: Currently available treatment methods for acute lung failure show high rates of complications. There is an urgent need for alternative treatment methods. A catheter device which can be minimal invasively inserted into the vena cava for intracorporeal gas exchange was developed. Main components of the device are a drive unit and a membrane module. In this study, the flow behavior in a vena cava model with inserted catheter prototype was investigated in experiments and basic computational fluid dynamic (CFD) simulations. Main findings are that the miniature blood pump has suitable characteristics and generates sufficient power to overcome the pressure drop induced in the membrane module, and that the design of the membrane outlet might be critical to avoid additional pressure losses. Parts manufactured with a high resolution 3D printer have proven to be suitable for the prototyping process.
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14:30-14:45, Paper ThCT13.5 | |
Design, Development, and Characterization of Breathforce: A Respiratory Training System for Patients with Spinal Cord Injuries |
Tran, Kevin | Univ. of Louisville |
Chen, Yangsheng | Kentucky Spinal Cord Injury Res. Center |
Ovechkin, Alexander | Univ. of Louisville |
Roussel, Thomas | Univ. of Louisville |
Keywords: Pulmonary and critical care - Pulmonary function testing & instrumentation, Pulmonary and critical care - Pulmonary rehabilitation
Abstract: In this effort, we report the development of a portable inspiratory-expiratory training device for use in rehabilitation of participants with cardiovascular and respiratory motor deficits. The device uses existing airway restriction components to establish a manually adjustable respiratory training apparatus with an integrated pressure sensor and custom software to direct and track therapy sessions. The battery-powered system promotes proven rehabilitation methodologies performed at the clinic in a platform translated to the at home setting for participants with spinal cord injuries
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14:45-15:00, Paper ThCT13.6 | |
Feasibility of a Post-Auricle Wireless Power System for Pediatric Mechanical Circulatory Support Pumps |
Valdovinos, John | California State Univ. Northridge |
Nagra, Simerjit | California State Univ. Northridge |
Hussain, Fatima | California State Univ. Northridge |
Alvarez, Isabel | CSUN |
Keywords: Cardiovascular, respiratory, and sleep devices - Implantables, Cardiovascular, respiratory, and sleep devices - Wearables, Cardiovascular, respiratory, and sleep devices - Therapeutics
Abstract: Heart failure (HF) affects approximately 12,000-35,000 children each year in the United States. The development of blood pumps has provided circulatory support for many adults suffering with HF until they receive a heart transplant. However, while the development of blood pumps for adults has led to fully-implantable continuous flow devices, blood pump technology for children has lagged significantly behind. One area for improving blood pump implantability in children is the use of wireless powering transfer systems (WPTS). These systems eliminate the power cord connecting the implanted blood pump to the external power supply. In adults, WPTS have decreased the number of power cord-related infections and have improved patient outcomes after pump implantation. Unfortunately, the components of these wireless systems are too large for children. In this paper we describe the preliminary work to develop a fully implantable WPTS specifically designed to power the Jarvik 2000 Child. Specifically, we design planar coils 36 um in thickness to be implanted in behind-the-ear fashion. An amplifier and rectifier circuit were also built to provide 15.7V and 0.5A of voltage and current to the pump.
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ThCT14 |
Meeting Room 322AB |
Ambulatory and Diagnostic Systems and Devices 2 (Theme9) |
Oral Session |
Chair: Srimathveeravalli, Govindarajan | Memorial Sloan-Kettering Cancer Center |
Co-Chair: Holmes, David | Mayo Clinic |
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13:30-13:45, Paper ThCT14.1 | |
Estimating Mini Mental State Examination Scores Using Game-Specific Performance Values: A Preliminary Study |
Jung, Hee-Tae | Univ. of Massachusetts Amherst |
LEE, HYUNSUK | WOORISOFT |
KIM, KWANGWOOK | WOORISOFT |
KIM, BYEONGIL | WOORISOFT |
Park, Sung Ji | Heeyeon Hospital |
ryu, taekyeong | Heeyeon Hospital |
KIM, YANGSOO | HEEYEON Hospital |
Lee, Sunghoon Ivan | Univ. of Massachusetts Amherst |
Keywords: Ambulatory diagnostic and therapeutic devices - Ambulatory and ADL technologies, Health technology management and assessment, Ambulatory diagnostic and therapeutic devices - Wireless telemetric systems
Abstract: Individuals with permanent cognitive impairment need to be evaluated and monitored. There exists a number of clinically validated cognitive assessment tools, but they often need to be administered by trained therapists in clinical settings. This serves as a major barrier for frequent, longitudinal monitoring of cognitive function. In this work, we introduce Neuro-World, a series of innovative 3D mobile games, that allows one to self-administer the assessment of his/her cognitive function. The game performance is analyzed and converted into a clinically-accepted measure of cognitive function (i.e., the Mini Mental State Examination (MMSE) score), improving the translational impact of the system in real-world clinical settings. To validate the feasibility of our approach, we collected game-specific performance data from 12 post-stroke patients, which was used to train a supervised machine learning model to estimate the corresponding MMSE score. Our experiment results showed a normalized root mean square error of 5.3% between the actual and estimated MMSE scores. This study enables new clinical and research opportunities for accurate longitudinal assessment of cognitive function via an interactive means of playing mobile games.
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13:45-14:00, Paper ThCT14.2 | |
Optimizing Mental Workload by Functional Near-Infrared Spectroscopy Based Dynamic Difficulty Adjustment |
Ung, Wei Chun | Univ. Teknologi PETRONAS |
Meriaudeau, fabrice | Univ. De Bourgogne |
Tang, Tong Boon | Univ. Teknologi PETRONAS |
Keywords: FNIR (functional near infra-red) spectroscopy and near-infrared scanning and assessment, Ambulatory Therapeutic Devices - Biofeedback and related technologies, Health technology - Verification and validation
Abstract: Gains of cognitive training may be eliminated due to mental fatigue. This paper reports the design and implementation of a functional near-infrared spectroscopy (fNIRS) – dynamic difficulty adjustment (DDA) system. A total of 25 healthy volunteers underwent two training sessions – one with fixed difficulty level of training (FDT) and one with neurofeedback training (NFT) using our fNIRS-DDA system. The workload in each training session was assessed using the National Aeronautics and Space Administration Task Load Index (NASA-TLX). Whilst sustaining mental task performance, the drop in oxygenation level observed in NFT subjects might indicate mental fatigue as they received higher NASA-TLX scores, especially in both mental demand and frustration subscales. In contrast, the oxygenation levels remained almost constant by NFT subjects throughout the experiment. This suggests that the proposed fNIRS-DDA system aided the participants in avoiding mental fatigue. Future studies will investigate if the system may prevent the progression of Alzheimer’s disease.
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14:00-14:15, Paper ThCT14.3 | |
Automated Measurement and Subtask Analysis of the Timed Up-And-Go Test in the Field of Geriatrics |
Ziegl, Andreas | AIT Austrian Inst. of Tech. GmbH |
Kastner, Peter | AIT Austrian Inst. of Tech |
Modre, Robert | ARC Seibersdorf Res. GmbH |
Schreier, Guenter | AIT Austrian Inst. of Tech. GmbH |
Keywords: Ambulatory Diagnostic devices - Point of care technologies, Ambulatory diagnostic and therapeutic devices - Ambulatory and ADL technologies
Abstract: Multimorbidity and age-physiological functional restrictions can lead to frailty and a loss of a self-determined life in elderly patients. The Timed Up-and-Go test (TUG) is a sensitive and specific measure of frailty and has also many other areas of application, for example in chronic diseases. Besides the measurement of the complete TUG time, the analysis of subtasks may also reveal important information about particular aspects of the health status of test subjects. We developed an ultrasonic-based device for performing the TUG automatically, which can be attached to the backrest of a chair. This device provides the total TUG time as well as the displacement-time data for all included subtasks. To prepare for its use in clinical studies, we performed a field test at a geriatric center. The goal was to confirm feasibility, i.e. to assess its application in real patients. Despite some improvement potential revealed by the field test, the concept turned out to be an appropriate method for monitoring the TUG time and its subtasks.
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14:15-14:30, Paper ThCT14.4 | |
Mobile Fall Risk Assessment Solution for Daily-Life Settings |
Similä, Heidi | VTT Tech. Res. Centre of Finland Ltd |
Immonen, Milla Sinikka | VTT Tech. Res. Centre of Finland |
Niemirepo, Timo | VTT Tech. Res. Centre of Finland Ltd |
Keywords: Ambulatory diagnostic and therapeutic devices - Ambulatory and ADL technologies, Ambulatory diagnostic devices - Wellness monitoring technologies
Abstract: Prevention of falls requires accurate means for fall risk assessment in order to identify persons at risk. This paper introduces a novel mobile fall risk assessment solution for daily-life settings. The solution contains an Android application that uses acceleration sensor data received via Bluetooth LE connection. The application guides through a simple walk test, analyzes the acceleration data measured from the acceleration sensor attached to the lower back and gives feedback about the fall risk for the user. Preliminary user tests with 12 healthy subjects were conducted to evaluate the feasibility of the solution. Each test subject performed three walks demonstrating normal, dragging and slow gait. The results showed that the acceleration features calculated by the application distinguish normal gait from dragging and slow gaits. Further collection of comprehensive data set with older adults is needed to adjust the application parameters appropriately for the target group.
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14:30-14:45, Paper ThCT14.5 | |
A New Smart Balance Rehabilitation System Technology Platform: Development and Preliminary Assessment of the Smarter Balance System for Home-Based Balance Rehabilitation for Individuals with Parkinson's Disease |
Alberto, Fung | Univ. of Houston |
Lai, Eugene | Houston Methodist Neurological Inst |
Lee, Beom-Chan | Univ. of Houston |
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14:45-15:00, Paper ThCT14.6 | |
Functional Near Infrared Spectroscopy in the Noninvasive Assessment of Brain Death |
Li, Ting | Chinese Acad. of Medical Science and Peking Union Medical Coll |
Pan, Boan | Univ. of Electronic Science and Tech. of China |
Keywords: FNIR (functional near infra-red) spectroscopy and near-infrared scanning and assessment, Ambulatory diagnostic devices - Oximetry
Abstract: Brain death, whose assessment is of great significance, is the irreversible loss of all the functions of the brain and brainstem. The traditional diagnostic methods mainly relies on complex, harmful or unstable test, including apnea test, evoked potential test, etc. Functional near infrared spectroscopy (fNIRS) utilize the good scattering properties of blood corpuscle to NIR, has the ability to monitor cerebral hemodynamics noninvasively. To objectively evaluate the brain death diagnosis with fNIRS, we use our portable fNIRS oximeter to measure the physiological data of fifteen brain death patients and twenty-two patients under natural state. The varied fractional concentration of inspired oxygen (FIO2) were provided in different phase. We found that the ratio of the concentration changes in oxy-hemoglobin to deoxy-hemoglobin (Δ[HbO2]/Δ[Hb]) in normal patients is significantly lower than brain death patients, and its restore oxygen change process in low-high-low paradigm is more remarkable. This resulting promotion indicates potential of fNIRS-measured hemodynamic index in diagnosing brain death.
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ThCT15 |
Meeting Room 323A |
Health Technologies (Theme9) |
Oral Session |
Chair: Holmes, David | Mayo Clinic |
Co-Chair: Cunha, Joao Paulo Silva | Inesc Tec, Pt 504 441 361 |
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13:30-13:45, Paper ThCT15.1 | |
Non-Invasive Method to Monitor Molecular Changes in Human Stratum Corneum During Acute Barrier Disruption Using Reflectance NIR Spectroscopy |
SHIN, Eui Seok | Samsung Advanced Inst. of Tech |
Lee, June-Young | Samsung Advanced Inst. of Tech |
Lee, Seung Jun | Samsung Advanced Inst. of Tech |
Nam, Sung Hyun | Samsung Advanced Inst. of Tech. Samsung Electronics |
Keywords: Health technology - Verification and validation, Clinical laboratory, assay and pathology technologies, Diagnostic devices - Physiological monitoring
Abstract: Stratum corneum is the outer most part of skin for barrier function. Disorder in stratum corneum is related with many skin diseases including acne, atopic dermatitis and psoriasis. In developed countries, about 20% of the population has disorder in the barrier function of stratum corneum. Adhesive tape stripping is a method to disrupt skin barrier function in studying disorder in stratum corneum. In this study, we obtained NIR (Near-Infrared) spectrum of human skin after tape stripping. Changes in skin spectra after barrier disruption were investigated through principal component analysis (PCA) of spectrum. PCA analysis revealed that peaks which account for –NH stretching and –CH vibration mainly contributed to the spectral variation caused by barrier disruption. Furthermore, second derivative spectrum analysis revealed that acute barrier disruption contributes to spectral changes in the region related with secondary structure of protein, lipid and water associated with lipid in stratum corneum. We demonstrated that acute barrier disruption affected features in NIR spectrum. These spectral changes revealed that acute barrier disruption affected keratin protein and ceramide in human stratum corneum. These results suggest that NIR spectroscopy can be used to monitor changes in filamentous network and lamellar structure in stratum corneum. NIR spectroscopy can provide non-invasive method to investigate skin disease related with barrier disruption by monitoring disturbance in protein and lipid structure in stratum corneum.
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13:45-14:00, Paper ThCT15.2 | |
On the Fly Reporting of Human Body Movement Based on Kinect V2 |
Rodrigues, Joana | Faculty of Engineering (FEUP), Univ. of Porto, Porto |
Maia, Paulo | Faculty of Engineering (FEUP), Univ. of Porto, Porto |
Choupina, Hugo Miguel Pereira | Univ. of Porto |
Cunha, Joao Paulo Silva | Inesc Tec, Pt 504 441 361 |
Keywords: Health technology management and assessment, Diagnostic devices - Physiological monitoring
Abstract: Human gait analysis is of utmost importance in understanding several aspects of human movement. In clinical practice, characterizing movement in order to obtain accurate and reliable information is a major challenge, and physicians usually rely on direct observation in order to evaluate a patient’s motor abilities. In this contribution, a system that can objectively analyze the patients gait and generate an on the fly, targeted and optimized gait analysis report is presented. It is an extension to an existing system that could be used without interfering with the healthcare environment, which did not provide any on the fly feedback to physicians. Patient data are acquired using Kinect v2, followed by data processing, gait specific feature extraction, ending with the generation of a quantitative on the fly report. To the best of our knowledge, the complete system fills the gap as a proper gait analysis system, i.e. a low-cost tool that can be applied without interfering with the healthcare environment, provide quantitative gait information and on the fly feedback to physicians through a motion quantification report that can be useful in multiple areas.
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14:00-14:15, Paper ThCT15.3 | |
Physiological Responses of the Youth Viewing a Japanese Garden |
ZHANG, Yawen | Hong Kong Univ. of Science and Tech |
LIU, Congcong | Hong Kong Univ. of Science and Tech |
HERRUP, Karl | Hong Kong Univ. of Science and Tech |
Shi, Bertram E | Hong Kong Univ. of Science and Tech |
Keywords: Diagnostic devices - Physiological monitoring, Health technology management and assessment, Clinical engineering
Abstract: Previous studies have demonstrated that exposure to a Japanese garden is a non-pharmacological measure to improve the behavioral symptoms of elderly people with dementia, and that Japanese gardens are significantly more effective than other environments. However, it is not clear whether Japanese gardens have similar effects in the young. To address this open question, we measured the physiological responses of university students when viewing a Japanese garden, and compared them to the same students’ responses when viewing a control space. We measured three physiological indicators of autonomous nervous system (ANS) activity: the electrocardiograph (ECG), the blood volume pulse (BVP) and the galvanic skin response (GSR). Our results suggest that the Japanese garden does not have as calming an effect on younger subjects as observed previously in elderly subjects. However, students did respond more positively to the Japanese garden than to an unstructured space. Ambient temperature was found to be a critical factor affecting heart rate and heart rate variability, but not other measures.
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14:15-14:30, Paper ThCT15.4 | |
Knee Extensor Muscular Activity Estimation During Different Walking Patterns: Flat Normal and Brisk Walking, Stair Climbing |
Cosentino, Sarah | Waseda Univ |
Kasai, Ritaro | Waseda Univ |
Gu, Zixi | Waseda Univ |
Sessa, Salvatore | Waseda Univ |
kawakami, Yasuo | Waseda Univ |
Takanishi, Atsuo | Waseda Univ |
Keywords: Ambulatory diagnostic devices - Wellness monitoring technologies, Ambulatory diagnostic and therapeutic devices - Ambulatory and ADL technologies, Muscle stimulation
Abstract: Preserving mobility, the ability to keep a correct posture and dynamic balance in order to walk properly, is fundamental to maintain autonomy in daily life. Based on the correlation between muscle groups and autonomy, previous research has suggested that maintaining muscular tone in knee extensors is critical. Continuous training of knee extensors during aging is therefore essential to maintain independence. In this work, it is hypothesized that it is possible to estimate knee extensor activity only from IMU data based on a simple lower limbs model. The accuracy of the knee extensor activity estimation algorithm has been tested using sEMG measurements as control data on three different walking patterns: normal walk, fast walk and stair climbing. Estimated knee torque area and measured muscular activity for each step were compared confirming a high estimation accuracy with a correlation efficient R = 0.80. Moreover, muscular activity can be divided based on intensity in three groups of statistically significant difference confirmed by the Steel-Dwass method. Future works should test the usability of the algorithm for different walking patterns, and use the collected data and the refined algorithm to implement a smart resistive device to increase knee extensor exertion during each walking pattern to the level necessary for sufficient extensor training.
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14:30-14:45, Paper ThCT15.5 | |
Long Distance Vital Signs Monitoring with Person Identification for Smart Home Solutions |
Szankin, Maciej | Intel Corp |
Kwasniewska, Alicja | Gdansk Univ. of Tech |
sirlapu, tejaswini | Intel |
Wang, Mingshan | Intel Corp |
Ruminski, Jacek | Gdansk Univ. of Tech |
Nicolas, Rey | Intel Corp |
Bartscherer, Marko | Intel Coorporation |
Keywords: Wearable or portable devices for vital signal monitoring, Plethysmography, Health technology - Verification and validation
Abstract: Imaging photoplethysmography has already been proved to be successful in short distance (below 1m). However, most of the real-life use cases of measuring vital signs require the system to work at longer distances, to be both more reliable and convenient for the user. The possible scenarios that system designers must have in mind include monitoring of the vital signs of residents in nursing homes, disabled people, who can't move, constant support for people regardless of the performed activity (e.g. during sleeping), infants, etc. In this work we verified the possibility of remote pulse estimation at a distance above 5m. Additionally, we integrated the deep learning algorithm for person tracking and identification, even when facial features are not visible. In this way, we enabled the collection of user specific measurements to create personalized vital signs patterns and we provided the support for monitoring of multiple people using one video stream. The preliminary results showed that it is possible to accurately (RMSE < 2.8 beats per minute) extract pulse from visible light sequences acquired with a webcam at a distance of 6m after applying a proper image pre-processing algorithm.
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14:45-15:00, Paper ThCT15.6 | |
Elevation Measurement of Laryngeal Prominence from Depth Images for Evaluating Swallowing Function |
Sugimoto, Chika | Yokohama National Univ |
Masuyama, Yuto | Yokohama National Univ |
Keywords: Health technology - Verification and validation, Health technology management and assessment
Abstract: A system which easily evaluates swallowing function is needed for the early diagnosis of deglutition disorder and the support for daily exercise for the purpose of its maintenance and recovery. We propose a method to measure laryngeal movement in a non-contact and non-invasive way with reasonable accuracy. To evaluate laryngeal elevation quantitatively, laryngeal prominence is detected from depth data by area extraction based on the classifier obtained by using a decision tree and optimum solution selection using species-based PSO. The elevation time and amount is calculated by tracking the laryngeal prominence. The laryngeal movement could be observed in persons with laryngeal prominence during water swallowing test.
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ThCT16 |
Meeting Room 323B |
Health Informatics - Ehealth (Theme 10) |
Oral Session |
Chair: Caon, Maurizio | Univ. of Applied Sciences and Arts Western Switzerland |
Co-Chair: Gu, Irene Y.H. | Chalmers Univ. of Tech |
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13:30-13:45, Paper ThCT16.1 | |
Improved Sparse Adaptive Algorithms for Accurate Non-Contact Heartbeat Detection Using Time-Window-Variation Technique |
Ye, Chen | Keio Univ |
Toyoda, Kentaroh | Keio Univ |
Ohtsuki, Tomoaki | Keio Univ |
Keywords: Health Informatics - eHealth, Sensor Informatics - Sensors and sensor systems, Sensor Informatics - Wireless sensors and systems
Abstract: Recently, a sparse adaptive algorithm termed zero-attracting sign least-mean-square (ZA-SLMS), has been clarified to be able to reconstruct robustly heartbeat spectrum by Doppler radar signal. However, since the strengths of noise evidently differ under different body motions, the sparse heartbeat spectra cannot be always acquired accurately by the constant regularization parameter (REPA) that balances the gradient correction and the sparse penalty, applying in the ZA-SLMS algorithm. In this paper, an improved ZA-SLMS algorithm is proposed by introducing adaptive REPA (AREPA), where the proportion of sparse penalty is adjusted based on the standard deviation of radar data. Moreover, to enhance the stability of heartbeat detection, a time-window-variation (TWV) technique is further introduced in the improved ZA-SLMS algorithm, considering the fact that the position of spectral peak associated with the heart rate (HR) is stable when the length of time window changes within a short period. Experimental results measured against five subjects validated that our proposal reliably improves the error of HR estimation than the standard ZA-SLMS algorithm.
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13:45-14:00, Paper ThCT16.2 | |
Co-Saliency-Enhanced Deep Recurrent Convolutional Networks for Human Fall Detection in E-Healthcare |
Ge, Chenjie | Chalmers Univ. of Tech |
Gu, Irene Y.H. | Chalmers Univ. of Tech |
Yang, Jie | Shanghai Jiaotong Univ |
Keywords: General and theoretical informatics - Pattern recognition, Health Informatics - eHealth, General and theoretical informatics - Deep learning and big data to knowledge
Abstract: This paper addresses the issue of fall detection from videos for e-healthcare and assisted-living. Instead of using conventional hand-crafted features from videos, we propose a fall detection scheme based on co-saliency-enhanced recurrent convolutional network (RCN) architecture for fall detection from videos. In the proposed scheme, a deep learning method RCN is realized by a set of Convolutional Neural Networks (CNNs) in segment-levels followed by a Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), to handle the time-dependent video frames. The co-saliency-based method enhances salient human activity regions hence further improves the deep learning performance. The main contributions of the paper include: (a) propose a recurrent convolutional network (RCN) architecture that is dedicated to the tasks of human fall detection in videos; (b) integrate a co-saliency enhancement to the deep learning scheme for further improving the deep learning performance; (c) extensive empirical tests for performance analysis and evaluation under different network settings and data partitioning. Experiments using the proposed scheme were conducted on an open dataset containing multicamera videos from different view angles, results have shown very good performance (test accuracy 98.96%). Comparisons with two existing methods have provided further support to the proposed scheme.
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14:00-14:15, Paper ThCT16.3 | |
Teenagers’ Usage of a Mobile-Wearable-Cloud Platform to Promote Healthy Lifestyles |
Caon, Maurizio | Univ. of Applied Sciences and Arts Western Switzerland |
Carrino, Stefano | Univ. of Applied Sciences and Arts Western Switzerland |
Angelini, Leonardo | Univ. of Applied Sciences and Arts Western Switzerland |
Abou Khaled, Omar | Univ. of Applied Sciences and Arts Western Switzerland |
Mugellini, Elena | Univ. of Applied Sciences and Arts Western Switzerland |
Velickovski, Filip | EURECAT |
Andreoni, Giuseppe | Pol. Di Milano |
Keywords: Health Informatics - eHealth, Health Informatics - Information technologies for healthcare delivery and management, Health Informatics - Preventive health
Abstract: In contemporary society, non-communicable diseases linked to unhealthy lifestyles, such as obesity, are on the rise with a major impact on global deaths. Prevention is the new frontier, promising to increase life expectancy and quality, while reducing costs related to healthcare. The PEGASO project developed a mobile ecosystem where the digital Companion aims at empowering teenagers in the adoption of healthy lifestyles. The pilot study conducted in three European countries (Spain, UK and Italy) shows a good acceptance of the system and that teenagers are keen to use mobile technology to improve their lifestyle, although wearable devices did not engage the young users.
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14:15-14:30, Paper ThCT16.4 | |
Seasonal Variation in an At-Home Telemonitoring Trial |
Argha, Ahmadreza | Univ. of New South Wales |
Celler, Branko George | Univ. of New South Wales |
Keywords: Health Informatics - eHealth, Health Informatics - Telehealth, Health Informatics - Health information systems
Abstract: This paper aims to present findings on seasonal variation in a recently completed Commonwealth Scientific and Industrial Research Organization (CSIRO) national trial of home telemonitoring of patients with chronic conditions, carried out at five locations along the east coast of Australia. Patients in this trial were selected from a list of eligible patients living with a range of chronic conditions. Each test patient was case matched with at least one control patient. A total of 114 test patients and 173 control patients were available in this trial. However, of the 287 patients, we only considered subjects who had one or more admissions in the years 2010-2012. Three different groups were analyzed because of substantially different climates, i.e. Queensland (QLD), Australian Capital Territory & Victoria (ACT + VIC), and Tasmania (TAS). Time series data were analyzed using linear regression for a period of 3 years before the intervention in order to obtain an average seasonal variation pattern.
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14:30-14:45, Paper ThCT16.5 | |
Increasing Health Care Adherence through Gamification, Video Feedback, and Real-World Rewards |
Saric, Kevin | CSIRO |
Redd, Christian Brandt | Commonwealth Scientific and Industrial Res. Organisation |
Varnfield, Marlien | CSIRO |
O'Dwyer, John | CSIRO |
Karunanithi, Mohanraj | CSIRO Digital Productivity Flagship |
Keywords: Health Informatics - eHealth, Health Informatics - Informatics for chronic disease management, Health Informatics - Mobile health
Abstract: Treatment non-adherence poses a sizeable and persistent challenge to health professionals. In the US alone, it is estimated that at least 100 billion per year is spent on avoidable health care costs with an additional 230 billion per year forfeited due to lost productivity. Efforts to increase adherence have yielded mixed results. We present an adaptable, theoretical framework that uses established gamification methods coupled with a means of motivating patients using real-world rewards. The framework presented herein is implemented via user interface modifications to a clinically validated health tracking app, as well as a means of delivering video feedback for viewing a variety of potential reward outcomes.
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ThCT17 |
Meeting Room 323C |
Sensing/Animal Models (Theme 7) |
Oral Session |
Chair: Oralkan, Omer | North Carolina State Univ |
Co-Chair: Inan, Omer | Georgia Inst. of Tech |
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13:30-13:45, Paper ThCT17.1 | |
Imaging of IR700DX Labeled Mouse Breast Tumor Using a Custom Angle-Selective Fluorescence Contact Imaging System |
Papageorgiou, Efthymios Philip | UC Berkeley |
Giverts, Simeon | UC Berkeley |
Zhang, Hui | UCSF |
Park, Catherine | UCSF |
Boser, Bernhard | UC Berkeley |
Anwar, Mekhail | UCSF |
Keywords: Optical and photonic sensors and systems, Integrated sensor systems, Sensor systems and Instrumentation
Abstract: Cancer treatment faces the challenge of identifying small clusters of residual tumor cells in the resection cavity after the gross section of tumor is surgically removed. Despite the introduction of targeted fluorescent probes to guide cancer surgeries, large, bulky, optical components restrict the ability of fluorescence imaging devices to detect small clusters of tumor cells in the complex surgical cavity. We have developed a small size-scale contact fluorescence image sensor that incorporates angle-selective gratings and a thin 15 um amorphous silicon optical wavelength filter for detecting residual cancer tissue in vivo. Using a custom fluorescent probe combining a fluorescent dye, IR700DX, with a targeted antibody, Trastuzumab, we label and visualize breast tissue in in vivo mouse models of breast cancer. When imaging tumor-bearing mice injected with the probe, HER2+ breast cancer tissue intensity is 3.8±0.8 times brighter than other tissue. Excised cancer tumors and residual cancer attached to healthy tissue are imaged using the custom image sensor. Residual cancer tissue can be detected in real-time and is imaged with a high SNR of 45 dB using an integration time of only 40 ms.
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13:45-14:00, Paper ThCT17.2 | |
A Conductance-Based Sensor to Estimate Bladder Volume in Felines |
McAdams, Ian | Cleveland Clinic |
Majerus, Steve | APT Center, Cleveland VAMC |
Zorman, Christian | Case Western Res. Univ |
Damaser, Margot S. | Lerner Res. Inst. the Cleveland Clinic Foundation |
Bourbeau, Dennis | FES Center, Cleveland VAMC |
Keywords: Bio-electric sensors - Sensing methods, Implantable sensors, Wearable low power, wireless sensing methods
Abstract: New research tools are essential to help understand the neural control of the lower urinary tract (LUT). A more nuanced understanding of the neuroanatomy of bladder function could enable new treatment options or neuroprosthesis to eliminate incontinence. Here we describe the design, prototyping and validation of a sensing mechanism for a catheter-free fluid volume estimating system for chronic neurophysiological studies of the lower urinary tract and ambulatory urodynamics. The system consists of two stimulation electrodes, one sensing anode, and a microcontroller for control and recording. The packaged device is small enough to be surgically implanted within the bladder lumen, where it does not inhibit bladder function nor inflict trauma. Benchtop evaluation of the conductance-sensing system in simulated bladder-like conditions has demonstrated that the system can predict intra-vesical fluid volume to within <5mL mean error below 40mL and worst-case mean error of 13mL near full-scale volume. These results indicate that conductance-based volume sensing of the urinary bladder is a feasible method for real-time measurement.
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14:00-14:15, Paper ThCT17.3 | |
Towards an Untethered Ultrasound Beamforming System for Brain Stimulation in Behaving Animals |
Seok, Chunkyun | North Carolina State Univ |
Ali, Ziad | North Carolina State Univ |
Yamaner, Feysel Yalcin | North Carolina State Univ |
Sahin, Mesut | New Jersey Inst. of Tech |
Oralkan, Omer | North Carolina State Univ |
Keywords: Acoustic sensors and systems, Implantable systems, Portable miniaturized systems
Abstract: In this paper, we present a wireless ultrasound transmit (TX) beamforming system, potentially enabling wearable brain stimulation for small awake/behaving animals. The system is comprised of a 16-element capacitive micromachined transducer (CMUT) array, driven by a custom phased-array integrated circuit (IC), which is capable of generating high-voltage (13.5 V) excitation signals with sixteen phase delays and four amplitude levels. In addition, a Bluetooth low-energy module and a power management unit were integrated into the system, which realizes a battery-operated self-contained unit. We validated the functionality of the system by demonstrating beamforming and steering with a hydrophone measurement setup. We achieved an acoustic pressure output of 554 kPapp at the depth of 5 mm, which corresponds to a spatial-peak pulse-average intensity (ISPPA) of 2.9 W/cm2. The measured 6-dB beamwidth (0.4 mm) is promising in that it can stimulate a specific region of the brain, especially for small animals such as mice. Further smart partitioning of the system will enable a truly wearable device for small animals.
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14:15-14:30, Paper ThCT17.4 | |
Evaluation of Bone Conduction Vibration System Using Photoacoustic Effec |
Wadamori, Naoki | Nagaoka Univ. of Tech |
Keywords: Acoustic sensors and systems
Abstract: This article proposes a novel bone conduction vibrator based on an interesting phenomenon where audible sound can be perceived when a vibration is produced using a laser beam that is synchronized to the sound and this vibration is transmitted to an auricular cartilage. To study this phenomenon, we measured the effect using a rubber sheet with similar properties to those of soft tissue, together with an acceleration sensor, and found that audible sound was produced in the sample. We also calculated the force level based on the mechanical impedance and the acceleration in the proposed system. It is expected that a force level equal to the reference equivalent threshold force level can be achieved at a light intensity below the safety limit for human skin exposure by choosing an irradiation wavelength at which a larger degree of optical absorption occurs. This novel application of the photoacoustic effect is promising for bone conduction hearing aids.
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14:30-14:45, Paper ThCT17.5 | |
Unobtrusive Heartbeat Detection from Mice Using Sensors Embedded in the Nest |
Gurel, Nil Zeynep | Georgia Inst. of Tech |
Jeong, Hyeon Ki | Georgia Inst. of Tech |
Kloefkorn, Heidi | Emory Univ |
Shawn, Hochman | Emory Univ |
Inan, Omer | Georgia Inst. of Tech |
Keywords: Physiological monitoring - Instrumentation, Sensor systems and Instrumentation, Physiological monitoring - Novel methods
Abstract: Unobtrusive monitoring of physio-behavioral variables from animals can minimize variability in preclinical research and thereby maximize the potential for clinical translation. In this paper, we present the design, implementation, and validation of an instrumented nest providing continuous recordings of seismocardiogram (SCG) signals and skin temperature. SCG represents the chest-wall vibrations associated with the heartbeat, and can potentially provide a measure by which individual heartbeats can be detected without the need for electrodes or implantable devices. A non-contact electric field sensor placed in proximity to the animal in the nest was also used to detect respiratory dynamics. The setup was tested with a total of six anesthetized mice. To understand the effects of mouse positioning within the nest on signal quality, the error in heartbeat detection at different positions of the sensor on the body was quantified, with a simultaneously-obtained electrocardiogram (ECG) as the reference standard. At the optimal placement determined with this approach, multiple perturbations were performed such as pinching, changing ambient temperature, and norepinephrine injection to modulate physiology and assess measurement capability. Heartbeat intervals obtained from the ECG and SCG during the perturbations were correlated (R2=0.82) and were in agreement according to Bland-Altman methods (bias: 0.006ms, 95% confidence interval: [-3.79, 3.78]ms) suggesting that SCG can be reliably used for unobtrusive heartbeat detection. Accordingly, the setup can provide a means by which individual heartbeats – and thereby heart rate and heart rate variability indices – can be quantified without the need for any sensors to be attached to the body of the animal.
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14:45-15:00, Paper ThCT17.6 | |
A Wireless Optoelectronic Neuroscience Platform for Chronic Fluorescence Sensing in Freely Behaving Rodents |
Noormohammadi Khiarak, Mehdi | Laval Univ |
Gagnon-Turcotte, Gabriel | Univ. Laval |
Martianova, Ekaterina | Laval Univ |
Bories, Cyril | Laval Univ |
Martel, Sylvain | Ec. Pol. De Montreal |
C. Proulx, Christophe | Laval Univ |
De Koninck, Yves | Laval Univ |
Gosselin, Benoit | Laval Univ |
Keywords: Optical and photonic sensors and systems, Implantable systems, Integrated sensor systems
Abstract: We present a new head mountable wireless fiber biophotometry microsystem conceived to detect fluorescent signal fluctuations correlated with neuronal activity. The proposed system incorporates all aspects of a conventional tethered fiber-based biophotometry system encompassed into a wireless microsystem. The interface includes an LED as excitation light source, a custom designed CMOS biosensor, a multimode fiber, a microcontroller (MCU), and a wireless data transceiver enclosed within a 3D-printed, small and light weight, plastic housing. Precisely, the system incorporates a new optoelectronic biosensor merging two individual building blocks, namely a low-noise sensing front-end and a 2nd order continuous-time Σ∆ modulator (CTSDM), into a single module for enabling high-sensitivity and high energy-efficiency photo-sensing. The proposed CMOS biosensor is implemented in a 0:18-µm CMOS technology, consuming 41 µW from a 1:8-V supply voltage, while achieving a peak dynamic range of 86 dB over a 50-Hz input bandwidth at a 20-kS=s sampling rate. This new interface opens new avenues for conducting in-vivo experiments with live animals.
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ThCT18 |
Meeting Room 324 |
Wearable Sensors (Theme 7) |
Oral Session |
Chair: Selvaraj, Nandakumar | Vital Connect Inc |
Co-Chair: Nallathambi, Gabriel | VitalConnect |
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13:30-13:45, Paper ThCT18.1 | |
A Novel Environment-Invariant Core Body Temperature Estimation for High Sensitivity and Specificity Fever Screening |
Silawan, Nawatt | Panasonic Corp. Automotive & Industrial Systems Company, |
Kusukame, Koichi | Panasonic Industrial Devices Singapore Tech. Centre |
Kek, Khai Jun | Panasonic Industrial Devices Singapore |
Kuan, Win Sen | National Univ. Hospital |
Keywords: Thermal sensors and systems, Optical and photonic sensors and systems, Physiological monitoring - Novel methods
Abstract: We propose a novel concept for core body temperature estimation to improve sensitivity and specificity of a fever screening system under different environmental conditions based on an infrared thermal camera. The conventional approach of setting low temperature thresholds to determine presence of fever to increase sensitivity has led to highly-degraded specificity due to the low accuracy in core body temperature estimation. Two main causes are the moderate correlation between core body temperature and surface temperature data used to determine it, and the estimation algorithm that does not consider changes in the environment. Hence, in our novel concept, we eliminate the environmental effects by using direct and correcting temperature data, and thus improve the accuracy in estimating core body temperature. The direct data contain rich information about core body temperature through maximum temperatures obtained from the mouth, ear, around the eye and forehead, while the correcting data contain information related to the surroundings such as the cheek and nose temperatures to compensate for the environmental effect on the former. Since direct data can be easily affected by the environment and noise, multiple direct data are taken to minimize this problem. Through improved accuracy, both sensitivity and specificity will be automatically increased and the trade-off between them when adjusting the threshold values will be greatly relaxed. Analysis of the results shows improvement in both sensitivity and specificity from 78.9% and 87.0%, respectively, in the conventional approach, to 84.2% and 91.3% in the proposed method when 37.5 deg C was set as the threshold. Data in the present study was obtained from a wide spectrum of ages (between 22 and 58 years), ethnicities (seven) and core body temperatures (36.0 deg C to 39.5 deg C). Data were also collected at variable room temperatures ranging from 20.2 deg C to 30.8 deg C.
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13:45-14:00, Paper ThCT18.2 | |
Polymer-Coated Fiber Optic Probe for the Monitoring of Breathing Pattern and Respiratory Rate |
Iacoponi, Sara | Univ. Campus Bio-Medico Di Roma |
Massaroni, Carlo | Univ. Campus Bio-Medico Di Roma |
Lo Presti, Daniela | Campus Bio-Medico Di Roma Univ |
Saccomandi, Paola | Univ. Campus Bio-Medico of Rome |
Caponero, Michele Arturo | ENEA - Centro Ricerche Frascati |
D'Amato, Rosaria | ENEA - Centro Ricerche Frascati |
Schena, Emiliano | Univ. of Rome Campus Bio-Medico |
Keywords: Optical and photonic sensors and systems, Chemo/bio-sensing - Biological sensors and systems, Mechanical sensors and systems
Abstract: In recent years, no-invasive and small size systems are meeting the demand of the new healthcare system, in which the vital signs monitoring is gaining in importance. In this context, Fiber Bragg grating (FBG) sensors are becoming very popular and FBG-based systems could be used for monitoring vital signs. At the same time, FBG could be able to sense chemical parameters by the polymer functionalization. The aim of our study was investigating the ability of a polymer-coated FBG-based probe for monitoring breathing patterns and respiratory rates. We tested the proposed FBG-based probe on 9 healthy volunteers during spirometry, the most common pulmonary function test. Results showed the high accuracy of the proposed probe to detect respiratory rate. The comparison between the respiratory rates estimated by the probe with the ones by the spirometer showed the absolute value of the percentage errors lower than 2.07% (in the 78% of cases <0.91%). Lastly, a Bland Altman analysis was performed to compare the instantaneous respiratory rate values gathered by the spirometer and the FBG probe showing the feasibility of breath-by-breath monitoring by the proposed probe. Results showed a bias of 0.06±2.90 breaths x min -1. Additionally, our system was able to follow the breathing activities and monitoring the breathing patterns.
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14:00-14:15, Paper ThCT18.3 | |
Detection of Respiratory Crackle Sounds Via an Android Smartphone-Based System |
Olvera-Montes, Nemecio Carlos | Univ. Autónoma Metropolitana |
Reyes, Bersaín Alexander | Univ. Autonoma De San Luis Potosi (UASLP) |
Charleston-Villalobos, Sonia | Univ. Autonoma Metropolitana |
Gonzalez-Camarena, Ramon | Univ. Autonoma Metropolitana |
Mejía Ávila, Mayra | Inst. Nacional De Enfermedades Res |
Dorantes Méndez, Guadalupe | Univ. Autónoma De San Luis Potosí |
Reulecke, Sina | Univ. Autónoma Metropolitana |
Aljama-Corrales, Tomas | Univ. Autonoma Metropolitana |
Keywords: Physiological monitoring - Novel methods, Physiological monitoring - Modeling and analysis, Physiological monitoring - Instrumentation
Abstract: Abstract—Pulmonary auscultation with traditional stethoscope, although useful, has limitations for detecting discontinuous adventitious respiratory sounds (crackles) that commonly occur in respiratory diseases. In this work, we present the development of a mobile health system for the automated detection of crackle sounds, comprised by an acoustical sensor, a smartphone device, and a mobile application (app) implemented in Android. The app allows the physician to record, store, reproduce, and analyze respiratory sounds directly on the smartphone. The algorithm for crackle detection was based on a time-varying autoregressive modeling. Performance of the automated detector was analyzed using synthetic fine and coarse crackle sounds randomly added to the basal respiratory sounds acquired from healthy subjects with different signal to noise ratios. Accuracy and sensitivity were found to range from 90.7% to 94.0% and from 91.2% to 94.2%, respectively. Application of the proposed mobile system to real acquired data from a patient with pulmonary fibrosis is also exemplified.
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14:15-14:30, Paper ThCT18.4 | |
A 3D-Printed, Adjustable-Stiffness Knee Brace with Embedded Magnetic Angle Sensor |
Bolus, Nicholas | Georgia Inst. of Tech |
Ganti, Venu | Georgia Inst. of Tech |
Inan, Omer | Georgia Inst. of Tech |
Keywords: Wearable sensor systems - User centered design and applications, Wearable body-compliant, flexible and printed electronics, Physiological monitoring - Instrumentation
Abstract: In this work, we detail the design and verification of a novel, 3D-printed, flexible knee brace with an embedded magnetic angle sensor for monitoring joint kinematics. The brace’s torsional stiffness can be selectively modified by applying elastic bands of varying thickness. Through benchtop tests and finite element analysis simulations, we characterize the mechanical behavior of the knee brace and determine estimates of torsional stiffness across a range of band thicknesses. To demonstrate the ability to modulate knee joint loading in a real-world scenario, we report results of a pilot study in which able-bodied subjects wear the device during treadmill walking and seated flexion-extension tasks.
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14:30-14:45, Paper ThCT18.5 | |
Clinical Validation of a Wearable Respiratory Rate Device for Neonatal Monitoring |
Raj, Antony | HTIC IIT Madras |
SP, Preejith | Healthcare Tech. Innovation Center - IITMadras |
Raja, Vijai Shankar | Helyxon Healthcare Solutions Pvt Ltd |
Joseph, Jayaraj | HTIC, Indian Inst. of Tech. Madras |
Sivaprakasam, Mohanasankar | Indian Inst. of Tech. Madras |
Keywords: Wearable sensor systems - User centered design and applications, Physiological monitoring - Instrumentation, Portable miniaturized systems
Abstract: Respiratory rate monitoring is of paramount importance in neonatal care. Manual counting of expansions and contractions of the abdomen or diaphragm of the neonate is still the widely accepted measure of respiratory rate in most clinical settings. A practical, affordable, easy-to-use technology to continuously measure respiratory rate in neonates is essential to recognize the signs and symptoms of respiratory disorders. Clinical validation of a system for continuous and long term respiratory rate monitoring of neonates, in a wearable form factor with capability of remote monitoring is presented in this paper. The respiratory rate monitor was validated in clinical settings on 10 premature babies with various disease conditions and respiratory rates varying from 25 to 90 breaths per minute. Results show a high degree of correlation between the respiratory rate measured by the device and reference measurements. An intelligent algorithm which can remove motion corruption from the accelerometer data and provide reliable results is essential for the large-scale adoption of the technology for both clinical as well as home monitoring. The technical details of implementation, results and analysis of the clinical study and observations made during clinical study regarding the feasibility of integrating the device in neonatal care are covered in this paper.
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14:45-15:00, Paper ThCT18.6 | |
Fully Disposable Wireless Patch Sensor for Continuous Remote Patient Monitoring |
Selvaraj, Nandakumar | Vital Connect Inc |
Nallathambi, Gabriel | VitalConnect |
Moghadam, Rod | VitalConnect Inc |
Aga, Arshan | VitalConnect Inc |
Keywords: Physiological monitoring - Novel methods, Physiological monitoring - Instrumentation, Wearable low power, wireless sensing methods
Abstract: Continuous remote monitoring with convenient wireless sensors is attractive for early detection of patient deterioration, preventing adverse events and leading to better patient care. This article presents an innovative sensor design of VitalPatch, a fully disposable wireless biosensor, for remote continuous monitoring, and details the performance assessments from bench testing and laboratory validation in 57 subjects. The bench testing results reveal that VitalPatch’s QRS detection had a positive predictive value of >99% from testing with ECG databases. The accuracies of HR, BR and skin temp (in mean absolute error, MAE) from bench testing were <5 bpm, <1 brpm, < 1◦C respectively. The laboratory testing in 57 subjects revealed the accuracy of HR and BR to be 2.2±1.5 bpm and 1.7±0.7 brpm respectively for stationary periods. The absolute percent error in detecting steps was 4.7±4.6%, and the accuracy in detecting posture was 96.4±3.1%. Meanwhile, the specificity and sensitivity of fall detection (n=20) was found to be 100% and 93.8%, respectively. In conclusion, VitalPatch biosensor demonstrated clinically acceptable accuracies for its vital signs and actigraphy metrics applicable for continuous unobtrusive patient monitoring.
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ThCT19 |
Meeting Room 325A |
Education and Career Development in in Biomedical Engineering (Theme 11) |
Oral Session |
Chair: Wheeler, Bruce | Univ. of Florida |
Co-Chair: Bassir Kazeruni, Neda, Mélanie | Columbia Univ |
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13:30-13:45, Paper ThCT19.1 | |
Designing a Hybrid Engineering Course Combining Case-Based and Lecture-Based Teaching |
Bassir Kazeruni, Neda, Mélanie | Columbia Univ |
Laboy, Andre | Columbia Univ |
Hess, Henry | Columbia Univ |
Keywords: Novel approaches to BME education, Teaching design, Instruction and learning
Abstract: Traditional engineering and business school courses have different pedagogical emphases. Engineering courses are perceived as technical, dense and require students to provide definitive answers to problems. On the other hand, business school courses aim to increase students’ knowledge by confronting them with real-world cases and by encouraging both in- and out-of-the-classroom teamwork, thinking in groups and problem solving. In business school courses, the teaching is directed towards the thought process rather than the final answer itself. These two approaches to learning are both valuable and give the opportunity to develop complementary skills. Combining both approaches in a single course is however challenging. We tackled this challenge by designing the semester-long “Introduction to Nanobiotechnology and Nanobioscience” course for senior undergraduate and first year graduate students as a hybrid class. Our objective was to design an engineering course of standard length, which incorporates key elements of the business schools’ case study approach to learning while retaining essential elements of the traditional engineering education.
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13:45-14:00, Paper ThCT19.2 | |
Engineering, Physical Therapy and the Community: A Service Learning Course |
Aceros, Juan | Univ. of North FLorida |
Lundy, Mary | Univ. of North Florida |
Rodriguez, Ayshka | Univ. of North Florida |
Keywords: Instruction and learning, Novel approaches to BME education, Teaching design
Abstract: The School of Engineering and the Physical Therapy program at the University of North Florida developed a novel, community-based course where undergraduate engineering students are partnered with physical therapy students. In this course students participate in hands-on, team-based design projects focused on low-tech and high-tech rehabilitation technology for children with disabilities. The impact of this interprofessional education experience on the students has been evaluated using the Public Service Motivation Scale for three years and its impact on the students is presented.
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14:00-14:15, Paper ThCT19.3 | |
Proposal for a New Training Exercise for Single Port Laparoscopic Cholecystectomy |
Amado, Lusvin | Pontifical Bolivarian Univ |
Salinas, Sergio Alexander | Univ. Pontificia Bolivariana-Seccional Bucaramanga |
PIMENTEL, ANIBAL | Pontificia Bolivariana - Clinica Chicamocha S.a |
Keywords: Teaching design, BME and global health, Instruction and learning
Abstract: This paper presents the design and implementation of a new training exercise to improve technical skills in the surgeons who perform Single Port Laparoscopic Cholecystectomy (SPLC), a technique that requires active improvements to overcome the lack of triangulation and collision of instruments both within and outside the abdominal cavity. The proposed mechanisms was developed based on peg transfer tests, performed by an expert surgeon in SPLC, with straight forceps and SILSTM access in a pelvitrainer, afterwards an unstructured interview was showed to the surgeon. These methodological tools provided the characteristics of the type of movement required by the peg transfer test at the time of performing the training task, which was taken as a reference to propose a new protocol to be implemented. The mentioned structure was tested by an expert surgeon, who performed 5 tasks, within an average running time of 170 seconds. At the end of the tests, a semi-structured interview was carried out again to the surgeon, where the improvement of the technique was tested.
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14:15-14:30, Paper ThCT19.4 | |
Activities to Invigorate a Student Chapter of the IEEE Engineering in Medicine and Biology Society |
Carlson, Charles | Kansas State Univ |
Lyle, Alexandra | Kansas State Univ |
Phillips, Gabrielle Johannah | Kansas State Univ |
Chappell, Jacob | Kansas State Univ |
Brown, Mariah | Kansas State Univ |
Fallahi, Hojjatollah | Kansas State Univ |
Wang, Shangxian | Kansas State Univ |
Suliman, Ahmad | Kansas State Univ |
Warren, Steve | Kansas State Univ |
Keywords: BME undergraduate research, Career development in BME, Instruction and learning
Abstract: An IEEE Engineering in Medicine and Biology Society (EMBS) student chapter can play an important service role for collegiate biomedical curricula, supporting (a) faculty and administrators as they offer biomedical programs and work to strengthen industry/community relationships, and (b) students as they engage in engineering skill development and seek industry employment, graduate school opportunities, or medical school placement. This paper summarizes recent projects and activities sponsored by the Kansas State University (KSU) Student Chapter of the IEEE EMBS – efforts intended to maintain interest in the student chapter while supporting its service role. Such a role will become more important in upcoming years in light of the increasing demand for biomedical engineers, especially in the Midwest United States, a reality which motivated the inception of a new KSU undergraduate degree in Biomedical Engineering starting in Fall 2018. The KSU IEEE EMBS student chapter can play a large role in the overall success of this new curriculum, and the projects and activities summarized in this paper are offered as examples to programs that may wish to benefit from an IEEE EMBS student chapter in a similar and meaningful way.
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14:30-14:45, Paper ThCT19.5 | |
How to Invent New Medical Devices |
Webster, John | Univ. of Wisconsin-Madison |
Keywords: Teaching design, Novel approaches to BME education, Instruction and learning
Abstract: Further develop strong engineering skills, supplement with knowledge of medicine and biology. Acquire clinical problems requiring solutions from medical and biological professionals. Form design teams to solve those problems: review the literature, confer with experts, brainstorm all the possibilities, select the most promising solution, build it in the lab, test it, iterate, publish.
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14:45-15:00, Paper ThCT19.6 | |
Integrated Information Rich Engineering Course Design |
Nizami, Shermeen | Carleton Univ |
Renon, Flavia | Carleton Univ |
Keywords: Novel approaches to BME education, Teaching design, Instruction and learning
Abstract: This study applies several high impact practices in an integrated fourth-year biomedical engineering course. The engineering design project is mapped to six deliverables using an adaptation of the Information Rich Engineering Design (IRED) model. This pedagogy facilitates regular student interactions with the instructor, the teaching assistant, the librarian and peers. Periodic information audits provide students with opportunities to reflect, integrate their learning, and share diverse experiences with the instructor. The term project is a real-world application which allows students to discover the relevance of theoretically learned concepts to hands-on problem solving. Students demonstrate competence in skills related to information seeking, writing and critical thinking through the completion of an IEEE-style conference paper.
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ThCT20 |
Meeting Room 325B |
Invited Session: Computational Human Models V. Tumor Treating Fields
(cd91k) |
Invited Session |
Chair: Bomzon, Ze'ev | Novocure |
Co-Chair: Wong, Eric T | Beth Israel Deaconess Medical Center |
Organizer: Makarov, Sergey | Electrical and Computer Engineering, Worcester Pol |
Organizer: Horner, Marc | ANSYS, Inc |
Organizer: Noetscher, Gregory | Worcester Pol. Inst |
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13:30-13:45, Paper ThCT20.1 | |
Advanced Multiparametric Imaging for Response Assessment to TTFields in Patients with Glioblastoma (I) |
mohan, suyash | Univ. of Pennsylvania |
Keywords: Medical devices interfacing with the brain or nerves, Wearable or portable devices for vital signal monitoring, Computer modeling for treatment planning
Abstract: Advanced Multiparametric imaging for response assessment to TTFields in patients with glioblastoma Suyash Mohan MD, PDCC Assistant Professor of Radiology & Neurosurgery Director, Neuroradiology Clinical Research Division Department of Radiology, Division of Neuroradiology Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, 19104, USA Introduction: Glioblastoma (GBM) is the most common malignant brain tumor and accounts for 70% of all primary brain tumors in adults. Despite aggressive multi-modal therapy including surgery, radiation, and chemotherapy, the prognosis remains poor with a median survival of around 2 years. Tumor treating fields (TTFields), is a new frontier in cancer therapy, and was recently approved for the treatment of GBM. This approach comprises of a portable device delivering low intensity and intermediate frequency alternating electric fields aiming at selectively inhibiting cellular proliferation of neoplastic cells, with minimal effect on the normal neurons. Promising findings of recent practice changing large-scale multinational randomized clinical trials have demonstrated that the addition of TTFields to maintenance temozolomide chemotherapy resulted in statistically significant improvement in progression-free survival (PFS) and overall survival (OS) compared to patients receiving standard chemo-radiation therapy (CRT). In this talk we will review the recent neuroimaging advances including novel physiologic and metabolic neuroimaging techniques and their role in monitoring treatment related temporal characteristics and assessing response to this unique treatment modality. The purpose of our study was to evaluate the effects of TTFields in GBM patients using diffusion tensor imaging (DTI), perfusion weighted imaging (PWI) and 3D-echoplanar spectroscopic imaging (EPSI). Methods: Twelve patients (both newly diagnosed & recurrent GBM patients) previously treated with standard of care maximal safe resection and CRT re
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13:45-14:00, Paper ThCT20.2 | |
Electroconductive Properties of Microtubules, Actin and Kinesin (I) |
Tuszynski, Jack Adam | Univ. of Alberta |
Keywords: Computer modeling for treatment planning, Computer model-based assessments for regulatory submissions, Models of therapeutic devices and systems
Abstract: We provide an overview of the modeling performed at both atomistic and coarse-grained levels in order to gain insight into electrostatic and electroconductive properties of the cytoskeleton. Computer simulations carried out for microtubules and actin filaments are presented. Charge and dipole values for monomers and dimers as well as polymerized forms of these proteins are summarized. Continuum approximations for cable equations describing actin filaments and microtubules compare favorably to measurements in buffer solutions showing soliton waves and transistor-like amplification of ionic signals. Conductivity and capacitance of tubulin and microtubules have been measured and modeled. A dramatic change in conductivity occurs when tubulin forms microtubules. In living cells, this signals a conductive phase transition coinciding with mitosis. Finally, we provide estimates of the forces, energies and power involved in the action of TTfields on microtubules and kinesin motors.
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14:00-14:15, Paper ThCT20.3 | |
Estimating the Intensity and Anisotropy of Tumor Treating Fields Using Matrix Decomposition. towards a More Comprehensive Estimation of Anti-Tumor Efficacy (I) |
Korshoej, Anders R. | Aarhus Univ. Hospital |
Thielscher, Axel | Copenhagen Univ. Hospital Hvidovre, Denmark & Biomedical En |
Keywords: Models of therapeutic devices and systems, Medical devices interfacing with the brain or nerves, Computer modeling for treatment planning
Abstract: Abstract— We present a novel approach for quantification the mean field intensity of tumor treating fields (TTFields) as well as unwanted effects from directional field correlation, indexed as fractional anisotropy (FA). I. INTRODUCTION TTFields is a non-invasive cancer treatment based on alternating electrical fields (100-300 kHz) induced by two sequentially active pairs of electrodes arrays placed on the body surface (1). Finite element (FE) field intensity estimation is used to quantify the “dose” of TTFields (2). However, fi | |