Concurrent surface electromyography and force myography classification during times of prosthetic socket shift and user fatigue

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dc.creatorSanford, Joe
dc.creatorPatterson, Rita M.
dc.creatorPopa, Dan O.
dc.date.accessioned2022-06-30T17:18:41Z
dc.date.available2022-06-30T17:18:41Z
dc.date.issued2017-08-01
dc.description.abstractObjective: Surface electromyography has been a long-standing source of signals for control of powered prosthetic devices. By contrast, force myography is a more recent alternative to surface electromyography that has the potential to enhance reliability and avoid operational challenges of surface electromyography during use. In this paper, we report on experiments conducted to assess improvements in classification of surface electromyography signals through the addition of collocated force myography consisting of piezo-resistive sensors. Methods: Force sensors detect intrasocket pressure changes upon muscle activation due to changes in muscle volume during activities of daily living. A heterogeneous sensor configuration with four surface electromyography-force myography pairs was investigated as a control input for a powered upper limb prosthetic. Training of two different multilevel neural perceptron networks was employed during classification and trained on data gathered during experiments simulating socket shift and muscle fatigue. Results: Results indicate that intrasocket pressure data used in conjunction with surface EMG data can improve classification of human intent and control of a powered prosthetic device compared to traditional, surface electromyography only systems. Significance: Additional sensors lead to significantly better signal classification during times of user fatigue, poor socket fit, as well as radial and ulnar wrist deviation. Results from experimentally obtained training data sets are presented.
dc.description.sponsorshipThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Science Foundation NRI (grant no. IIS-1208623).
dc.identifier.citationSanford, J., Patterson, R., & Popa, D. O. (2017). Concurrent surface electromyography and force myography classification during times of prosthetic socket shift and user fatigue. Journal of rehabilitation and assistive technologies engineering, 4, 2055668317708731. https://doi.org/10.1177/2055668317708731
dc.identifier.issn2055-6683
dc.identifier.urihttps://hdl.handle.net/20.500.12503/31247
dc.identifier.volume4
dc.publisherSage Publications
dc.relation.urihttps://doi.org/10.1177/2055668317708731
dc.rights.holderCopyright © The Author(s) 2017
dc.rights.licenseAttribution-NonCommercial 4.0 International (CC BY-NC 4.0)
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.sourceJournal of Rehabilitation Assistive Technologies Engineering
dc.subjecthand biomechanics
dc.subjecthuman machine interface
dc.subjectphysical human-robot interaction
dc.subjectpressure sensitive robot skin
dc.subjectprosthetic device
dc.titleConcurrent surface electromyography and force myography classification during times of prosthetic socket shift and user fatigue
dc.typeArticle
dc.type.materialtext

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