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Evaluating subsampling strategies for sEMG-based prediction of voluntary muscle contractions

Risto, Koiva and Barbara, Hilsenbeck and Claudio, Castellini (2013) Evaluating subsampling strategies for sEMG-based prediction of voluntary muscle contractions. In: Proceedings of ICORR - International Conference on Rehabilitation Robotics, pp. 1-7. IEEE. ICORR 2013, Seattle, WA, USA.

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Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6650492

Abstract

In previous work we showed that some human Voluntary Muscle Contractions (VMCs) of high interest to the prosthetics community, namely finger flexions/extensions and thumb rotation, can be effectively predicted using muscle activation signals coming from surface electromyography (sEMG). In this paper we study the effectiveness of various subsampling strategies to limit the size of the training data set, with the aim of extending the approach to an online VMC-prediction system whose main application will be force-controlled hand prostheses. We performed an experiment in which 10 ablebodied participants flexed and extended their fingers according to a visual stimulus, while muscle activations and VMCs (represented as synergistic fingertip forces) were gathered using sEMG electrodes and a custom-built measurement device. A Support Vector Machine (SVM) was trained on a fixed-sized subset of the collected data, obtained using seven different subsampling strategies. The SVM was then tested on subsequent new data. Our experimental results show that two subsampling strategies attain a prediction error as low as 6% to 12%, which is comparable to the error values obtained in our previous work when the entire data set was used and processed offline.

Item URL in elib:https://elib.dlr.de/85234/
Document Type:Conference or Workshop Item (Poster)
Title:Evaluating subsampling strategies for sEMG-based prediction of voluntary muscle contractions
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Risto, KoivaCIT-EC BielefeldUNSPECIFIED
Barbara, HilsenbeckDLRUNSPECIFIED
Claudio, CastelliniDLRUNSPECIFIED
Date:2013
Journal or Publication Title:Proceedings of ICORR - International Conference on Rehabilitation Robotics
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 1-7
Publisher:IEEE
Status:Published
Keywords:electromyography, machine learning, rehabilitation, prosthetics
Event Title:ICORR 2013
Event Location:Seattle, WA, USA
Event Type:international Conference
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Vorhaben Multisensorielle Weltmodellierung
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Perception and Cognition
Deposited By: Castellini, Dr. Claudio
Deposited On:16 Dec 2013 18:15
Last Modified:31 Jul 2019 19:42

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