EMBC'11 Paper Abstract

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Paper ThC3.1

De Rossi, Danilo (University of Pisa), lorussi, federico (University of Pisa), tognetti, alessandro (University of Pisa), carbonaro, nicola (university of pisa), anania, gaetano (Centro Piaggio - Università di Pisa)

Enhancing the Performance of Upper Limb Gesture Reconstruction Sensory Fusion

Scheduled for presentation during the Invited Session "Wearable Systems for Neuro-Rehabilitation – Reaching and Grasping" (ThC3), Thursday, September 1, 2011, 13:00−13:15, Essex Ballroom South Westin

33rd Annual International IEEE EMBS Conference, August 30 - September 3, 2011, Boston Marriott Copley Place, Boston, MA, USA

This information is tentative and subject to change. Compiled on June 26, 2019

Keywords Human performance - Activities of daily living, Wearable systems for neurorehabilitation - Reaching and grasping, Human performance - Engineering

Abstract

In this paper a novel method devoted to the recon- struction of the joint angles in a kinematic chain is described. The reconstruction algorithm is based on the fusion of the information deriving from inertial sensors (accelerometers) and conductive elastomer strain sensors. Accelerometers provide a reliable reconstruction when they are employed as inclinometer in quasi-static conditions. They suffer from artifacts when they are used to detect fast movements or when interactions with the environment occur. Generally, these artifacts have the form of rapid spikes with characteristic frequency components. The knowledge of the frequency components of the movement to be detected permits to remove these artifacts. Conversely, conductive elastomer sensors have a complex dynamic response, but they can easily provide the frequency content of the movement to be detected. A filtering strategy of the inertial sensor signals based on the elastomer sensor response provides a reliable reconstruction of joint variables during the movement.

 

 

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