Evaluation of myoelectric control learning using multi-session game-based training

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dc.contributor.authorTabor, Aaron
dc.contributor.authorBateman, Scott
dc.contributor.authorScheme, Erik
dc.date.accessioned2023-12-21T19:05:44Z
dc.date.available2023-12-21T19:05:44Z
dc.date.issued2018-07-12
dc.description.abstractWhile training is critical for ensuring initial success as well as continued adoption of a myoelectric powered prosthesis, relatively little is known about the amount of training that is necessary. In previous studies, participants have completed only a small number of sessions, leaving doubt about whether the findings necessarily generalize to a longer-term clinical training program. Furthermore, a heavy emphasis has been placed on a functional prosthesis use when assessing the effectiveness of myoelectric training. Although well-motivated, this all-inclusive approach may obscure more subtle improvements made in underlying muscle control that could lead to tangible benefits. In this paper, a deeper exploration of the effects of myoelectric training was performed by following the progress of 30 participants as they completed a series of ten 30-min training sessions over multiple days. The progress was assessed using a newly developed set of metrics that was specifically designed to quantify the aspects of muscle control that are foundational to the strong myoelectric prosthesis use. It was determined that, while myoelectric training can lead to improvements in muscle control, these improvements may take longer than previously considered, even occurring after improvements in the training game itself. These results suggest the need to reconsider how and when transfer from training activities is assessed.
dc.description.copyright© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/37613
dc.language.isoen
dc.publisherIEEE
dc.relationNatural Sciences and Engineering Research Council of Canada
dc.relationNew Brunswick Innovation Foundation
dc.relation.hasversionhttps://doi.org/10.1109/TNSRE.2018.2855561
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineElectrical and Computer Engineering
dc.titleEvaluation of myoelectric control learning using multi-session game-based training
dc.typejournal article
oaire.citation.endPage1689
oaire.citation.issue9
oaire.citation.startPage1680
oaire.citation.titleIEEE Transactions on Neural Systems and Rehabilitation Engineering
oaire.citation.volume26
oaire.license.conditionother
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85

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