RT Conference Proceedings
T1 Electromyographic indices of muscle fatigue of a severely paralyzed chronic stroke patient undergoing upper limb motor rehabilitation
A1 Ray, Andreas M.
A1 Maillot, Aurélien
A1 Helmhold, Florian
A1 Mahmoud, Wala Jaser
A1 López-Larraz, Eduardo
A1 Ramos-Murguialday, Ander
AB Modern approaches to motor rehabilitation of severe upper limb paralysis in chronic stroke decode movements from electromyography for controlling rehabilitation orthoses. Muscle fatigue is a phenomenon that influences these neurophysiological signals and may diminish the decoding quality. Characterization of these potential signal changes during movement patterns of rehabilitation training could therefore help improve the decoding accuracy. In the present work we investigated how electromyographic indices of muscle fatigue in the Deltoid Anterior muscle evolve during typical forward reaching movements of a rehabilitation training in healthy subjects and a stroke patient. We found that muscle fatigue in healthy subjects changed the neurophysiological signal. In the patient, however, no consistent change was observed over several sessions.
PB IEEE Computer Society
SN 9781538679210
SN 1948-3546
YR 2019
FD 2019-05-16
LK https://hdl.handle.net/11556/1748
UL https://hdl.handle.net/11556/1748
LA eng
NO Ray , A M , Maillot , A , Helmhold , F , Mahmoud , W J , López-Larraz , E & Ramos-Murguialday , A 2019 , Electromyographic indices of muscle fatigue of a severely paralyzed chronic stroke patient undergoing upper limb motor rehabilitation . in 9th International IEEE EMBS Conference on Neural Engineering, NER 2019 . , 8717165 , International IEEE/EMBS Conference on Neural Engineering, NER , vol. 2019-March , IEEE Computer Society , pp. 126-129 , 9th International IEEE EMBS Conference on Neural Engineering, NER 2019 , San Francisco , United States , 20/03/19 . https://doi.org/10.1109/NER.2019.8717165
NO conference
NO Publisher Copyright: © 2019 IEEE.
NO This study was funded by the Bundesministerium für Bildung und Forschung BMBF MOTORBIC (FKZ 13GW0053) and AMORSA (FKZ 16SV7754), the Deutsche Forschungsgemeinschaft (DFG), the fortüne-Program of the University of Tübingen (2422-0-0 and 2452-0-0), and the Basque Government Science Program (EXOTEK: KK 2016/00083).
DS TECNALIA Publications
RD 26 jul 2024