Real-time robustness evaluation of regression based myoelectric control against arm position change and donning/doffing

dc.contributor.authorHwang, Han-Jeong
dc.contributor.authorHahne, Janne Mathias
dc.contributor.authorMüller, Klaus-Robert
dc.date.accessioned2018-01-17T09:11:45Z
dc.date.available2018-01-17T09:11:45Z
dc.date.issued2017
dc.description.abstractThere are some practical factors, such as arm position change and donning/doffing, which prevent robust myoelectric control. The objective of this study is to precisely characterize the impacts of the two representative factors on myoelectric controllability in practical control situations, thereby providing useful references that can be potentially used to find better solutions for clinically reliable myoelectric control. To this end, a real-time target acquisition task was performed by fourteen subjects including one individual with congenital upper-limb deficiency, where the impacts of arm position change, donning/doffing and a combination of both factors on control performance was systematically evaluated. The changes in online performance were examined with seven different performance metrics to comprehensively evaluate various aspects of myoelectric controllability. As a result, arm position change significantly affects offline prediction accuracy, but not online control performance due to real-time feedback, thereby showing no significant correlation between offline and online performance. Donning/doffing was still problematic in online control conditions. It was further observed that no benefit was attained when using a control model trained with multiple position data in terms of arm position change, and the degree of electrode shift caused by donning/doffing was not severely associated with the degree of performance loss under practical conditions (around 1 cm electrode shift). Since this study is the first to concurrently investigate the impacts of arm position change and donning/doffing in practical myoelectric control situations, all findings of this study provide new insights into robust myoelectric control with respect to arm position change and donning/doffing.en
dc.description.sponsorshipDFG, 325093850, Open Access Publizieren 2017 - 2018 / Technische Universität Berlinde
dc.identifier.issn1932-6203
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/7329
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-6602
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc006 Spezielle Computerverfahrende
dc.subject.otherprostheticsen
dc.subject.otherelectromyographyen
dc.subject.otherarmsen
dc.subject.otherwristen
dc.subject.otheralgorithmsen
dc.subject.otherlinear regression analysisen
dc.subject.othercontrol systemsen
dc.subject.otherelectrode potentialsen
dc.titleReal-time robustness evaluation of regression based myoelectric control against arm position change and donning/doffingen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumbere0186318en
dcterms.bibliographicCitation.doi10.1371/journal.pone.0186318en
dcterms.bibliographicCitation.issue11en
dcterms.bibliographicCitation.journaltitlePLoS oneen
dcterms.bibliographicCitation.originalpublishernamePLoSen
dcterms.bibliographicCitation.originalpublisherplaceLawrence, Kan.en
dcterms.bibliographicCitation.volume12en
tub.accessrights.dnbfreeen
tub.affiliationFak. 4 Elektrotechnik und Informatik::Inst. Softwaretechnik und Theoretische Informatik::FG Maschinelles Lernende
tub.affiliation.facultyFak. 4 Elektrotechnik und Informatikde
tub.affiliation.groupFG Maschinelles Lernende
tub.affiliation.instituteInst. Softwaretechnik und Theoretische Informatikde
tub.publisher.universityorinstitutionTechnische Universität Berlinen

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