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Dynamic Elbow Flexion Force Estimation Through a Muscle Twitch Model and sEMG in a Fatigue Condition

Authors
Na, YoungjinKim, Jung
Issue Date
Sep-2017
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, v.25, no.9, pp 1431 - 1439
Pages
9
Journal Title
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
Volume
25
Number
9
Start Page
1431
End Page
1439
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/146960
DOI
10.1109/TNSRE.2016.2628373
ISSN
1534-4320
1558-0210
Abstract
We propose a joint force estimation method to compute elbow flexion force using surface electromyogram (sEMG) considering time-varying effects in a fatigue condition. Muscle fatigue is a major cause inducing sEMG changes with respect to time over long periods and repetitive contractions. The proposed method composed the muscle-twitch model representing the force generated by a single spike and the spikes extracted from sEMG. In this study, isometric contractions at six different joint angles (10 subjects) and dynamic contractions with constant velocity (six subjects) were performed under non-fatigue and fatigue conditions. Performance of the proposed method was evaluated and compared with that of previous methods using mean absolute value (MAV). The proposed method achieved average 6.7 +/- 2.8 % RMSE for isometric contraction and 15.6 +/- 24.7% RMSE for isokinetic contraction under fatigue condition with more accurate results than the previous methods.
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