Alternative muscle synergy patterns of upper limb amputees.

Autor: Wang X; Department of Orthopedics and Traumatology, LKS Faculty of Medicine, The University of Hong Kong, 999077 Hong Kong, China., Wang J; Department of Orthopedics and Traumatology, LKS Faculty of Medicine, The University of Hong Kong, 999077 Hong Kong, China.; Orthopedics Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, 518000 China., Fei N; Department of Orthopedics and Traumatology, LKS Faculty of Medicine, The University of Hong Kong, 999077 Hong Kong, China., Duanmu D; Department of Orthopedics and Traumatology, LKS Faculty of Medicine, The University of Hong Kong, 999077 Hong Kong, China., Feng B; Department of Orthopedics and Traumatology, LKS Faculty of Medicine, The University of Hong Kong, 999077 Hong Kong, China., Li X; Department of Orthopedics and Traumatology, LKS Faculty of Medicine, The University of Hong Kong, 999077 Hong Kong, China.; Orthopedics Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, 518000 China., Ip WY; Department of Orthopedics and Traumatology, LKS Faculty of Medicine, The University of Hong Kong, 999077 Hong Kong, China., Hu Y; Department of Orthopedics and Traumatology, LKS Faculty of Medicine, The University of Hong Kong, 999077 Hong Kong, China.; Orthopedics Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, 518000 China.
Jazyk: angličtina
Zdroj: Cognitive neurodynamics [Cogn Neurodyn] 2024 Jun; Vol. 18 (3), pp. 1119-1133. Date of Electronic Publication: 2023 Apr 26.
DOI: 10.1007/s11571-023-09969-5
Abstrakt: Myoelectric hand prostheses are effective tools for upper limb amputees to regain hand functions. Much progress has been made with pattern recognition algorithms to recognize surface electromyography (sEMG) patterns, but few attentions was placed on the amputees' motor learning process. Many potential myoelectric prostheses users could not fully master the control or had declined performance over time. It is possible that learning to produce distinct and consistent muscle activation patterns with the residual limb could help amputees better control the myoelectric prosthesis. In this study, we observed longitudinal effect of motor skill learning with 2 amputees who have developed alternative muscle activation patterns in response to the same set of target prosthetic actions. During a 10-week program, amputee participants were trained to produce distinct and constant muscle activations with visual feedback of live sEMG and without interaction with prosthesis. At the end, their sEMG patterns were different from each other and from non-amputee control groups. For certain intended hand motion, gradually reducing root mean square (RMS) variance was observed. The learning effect was also assessed with a CNN-LSTM mixture classifier designed for mobile sEMG pattern recognition. The classification accuracy had a rising trend over time, implicating potential performance improvement of myoelectric prosthesis control. A follow-up session took place 6 months after the program and showed lasting effect of the motor skill learning in terms of sEMG pattern classification accuracy. The results indicated that with proper feedback training, amputees could learn unique muscle activation patterns that allow them to trigger intended prosthesis functions, and the original motor control scheme is updated. The effect of such motor skill learning could help to improve myoelectric prosthetic control performance.
(© The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)
Databáze: MEDLINE
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