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dc.contributor.authorThacham-Poyil, Azeemsha
dc.contributor.authorSteuber, Volker
dc.contributor.authorAmirabdollahian, Farshid
dc.date.accessioned2020-03-26T01:07:59Z
dc.date.available2020-03-26T01:07:59Z
dc.date.issued2020-03-16
dc.identifier.citationThacham-Poyil , A , Steuber , V & Amirabdollahian , F 2020 , ' Influence of Muscle Fatigue on Electromyogram-Kinematic Correlation During Robot-Assisted Upper Limb Training ' , Journal of Rehabilitation and Assistive Technologies Engineering . https://doi.org/10.1177%2F2055668320903014
dc.identifier.issn2055-6683
dc.identifier.otherPURE: 18765740
dc.identifier.otherPURE UUID: 22576e32-ca3a-4c20-ac9b-3a8ff61bf5c8
dc.identifier.urihttp://hdl.handle.net/2299/22500
dc.description© The Author(s) 2020. Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us. sagepub.com/en-us/nam/open-access-at-sage).
dc.description.abstractIntroduction: Studies on adaptive robot-assisted upper limb training interactions do not often consider the implications of muscle fatigue sufficiently. Methods: In order to explore this, we initially assessed muscle fatigue in 10 healthy subjects using electromyogram features (average power and median power frequency) during an assist-as-needed interaction with HapticMASTER robot. Spearman’s correlation study was conducted between EMG average power and kinematic force components. Since the robotic assistance resulted in a variable fatigue profile across participants, a completely tiring experiment, without a robot in the loop, was also designed to confirm the results. Results: A significant increase in average power and a decrease in median frequency were observed in the most active muscles. Average power in the frequency band of 0.8-2.5Hz and median frequency in the band of 20-450Hz are potential fatigue indicators. Also, comparing the correlation coefficients across trials indicated that correlation was reduced as the muscles were fatigued. Conclusions: Robotic assistance based on user’s performance has resulted in lesser muscle fatigue, which caused an increase in the EMG-force correlation. We now intend to utilize the electromyogram and kinematic features for the auto-adaptation of therapeutic human-robot interactions.en
dc.language.isoeng
dc.relation.ispartofJournal of Rehabilitation and Assistive Technologies Engineering
dc.rightsOpen
dc.subjectHuman-Computer Interaction
dc.subjectRehabilitation
dc.titleInfluence of Muscle Fatigue on Electromyogram-Kinematic Correlation During Robot-Assisted Upper Limb Trainingen
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionAdaptive Systems
dc.contributor.institutionSchool of Engineering and Computer Science
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionCentre of Data Innovation Research
dc.description.statusPeer reviewed
dc.relation.schoolSchool of Engineering and Computer Science
dc.description.versiontypeFinal Published version
dcterms.dateAccepted2020-03-16
rioxxterms.versionVoR
rioxxterms.versionofrecordhttps://doi.org/10.1177%2F2055668320903014
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by-nc/4.0/
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeOpen


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