Myoelectric control and neuromusculoskeletal modeling: Complementary technologies for rehabilitation robotics
dc.citation.articleNumber | 100313 | en_US |
dc.citation.journalTitle | Current Opinion in Biomedical Engineering | en_US |
dc.citation.volumeNumber | 19 | en_US |
dc.contributor.author | Berning, Jeffrey | en_US |
dc.contributor.author | Francisco, Gerard E. | en_US |
dc.contributor.author | Chang, Shuo-Hsiu | en_US |
dc.contributor.author | Fregly, Benjamin J. | en_US |
dc.contributor.author | O'Malley, Marcia K. | en_US |
dc.date.accessioned | 2021-08-16T15:51:00Z | en_US |
dc.date.available | 2021-08-16T15:51:00Z | en_US |
dc.date.issued | 2021 | en_US |
dc.description.abstract | Stroke and spinal cord injury (SCI) are a leading cause of disability in the United States, and researchers have pursued using robotic devices to aid rehabilitation efforts for resulting upper-extremity impairments. To date, however, robotic rehabilitation of the upper limb has produced only limited improvement in functional outcomes compared to traditional therapy. This paper explores the potential of myoelectric control and neuromusculoskeletal modeling for robotic rehabilitation using the current state of the art of each individual field as evidence. Continuing advances in the fields of myoelectric control and neuromusculoskeletal modeling offer opportunities for further improvements of rehabilitation robot control strategies. Specifically, personalized neuromusculoskeletal models driven by a subject's electromyography signals may provide accurate predictions of the subject's muscle forces and joint moments, which, when used to design novel control strategies, could yield new approaches to robotic therapy for stroke and SCI that surpass the efficacy of traditional therapy. | en_US |
dc.identifier.citation | Berning, Jeffrey, Francisco, Gerard E., Chang, Shuo-Hsiu, et al.. "Myoelectric control and neuromusculoskeletal modeling: Complementary technologies for rehabilitation robotics." <i>Current Opinion in Biomedical Engineering,</i> 19, (2021) Elsevier: https://doi.org/10.1016/j.cobme.2021.100313. | en_US |
dc.identifier.doi | https://doi.org/10.1016/j.cobme.2021.100313 | en_US |
dc.identifier.uri | https://hdl.handle.net/1911/111175 | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Elsevier. | en_US |
dc.subject.keyword | Robotic rehabilitation | en_US |
dc.subject.keyword | Upper limb motor impairment | en_US |
dc.subject.keyword | Electromyography | en_US |
dc.subject.keyword | Neuromusculoskeletal modeling | en_US |
dc.title | Myoelectric control and neuromusculoskeletal modeling: Complementary technologies for rehabilitation robotics | en_US |
dc.type | Journal article | en_US |
dc.type.dcmi | Text | en_US |
dc.type.publication | post-print | en_US |
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