Electromyographic indices of muscle fatigue of a severely paralyzed chronic stroke patient undergoing upper limb motor rehabilitation

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dc.contributor.authorRay, Andreas M.
dc.contributor.authorMaillot, Aurélien
dc.contributor.authorHelmhold, Florian
dc.contributor.authorMahmoud, Wala Jaser
dc.contributor.authorLópez-Larraz, Eduardo
dc.contributor.authorRamos-Murguialday, Ander
dc.contributor.institutionMedical Technologies
dc.date.accessioned2024-07-24T11:48:15Z
dc.date.available2024-07-24T11:48:15Z
dc.date.issued2019-05-16
dc.descriptionPublisher Copyright: © 2019 IEEE.
dc.description.abstractModern 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.en
dc.description.sponsorshipThis 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).
dc.description.statusPeer reviewed
dc.format.extent4
dc.identifier.citationRay , 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
dc.identifier.citationconference
dc.identifier.doi10.1109/NER.2019.8717165
dc.identifier.isbn9781538679210
dc.identifier.issn1948-3546
dc.identifier.urihttps://hdl.handle.net/11556/1748
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85066740016&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherIEEE Computer Society
dc.relation.ispartof9th International IEEE EMBS Conference on Neural Engineering, NER 2019
dc.relation.ispartofseriesInternational IEEE/EMBS Conference on Neural Engineering, NER
dc.relation.projectIDDeutsche Forschungsgemeinschaft, DFG
dc.relation.projectIDEberhard Karls Universität Tübingen, 2422-0-0-2452-0-0
dc.relation.projectIDBundesministerium für Bildung und Forschung, BMBF, FKZ 13GW0053-FKZ 16SV7754
dc.relation.projectIDEusko Jaurlaritza, KK 2016/00083
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsArtificial Intelligence
dc.subject.keywordsMechanical Engineering
dc.subject.keywordsSDG 3 - Good Health and Well-being
dc.titleElectromyographic indices of muscle fatigue of a severely paralyzed chronic stroke patient undergoing upper limb motor rehabilitationen
dc.typeconference output
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