Robustness of Muscle Synergies under Variant Muscle Contraction Force during Forearm Movements

被引:0
|
作者
Deng, Hanjie [1 ]
Cheung, Vincent C. K. [1 ]
Geng, Yanjuan [1 ]
Samuel, Mojisola G. Asogbon [1 ]
Samuel, Oluwarotimi Williams [1 ]
Li, Guanglin [1 ]
机构
[1] Chinese Acad Sci, Key Lab Human Machine Intelligence Synergy Syst, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China
基金
中国国家自然科学基金;
关键词
MYOELECTRIC PATTERN-RECOGNITION; HAND;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The Electromyography-based Pattern-Recognition (EMG-PR) framework has been investigated for almost three decades towards developing an intuitive myoelectric prosthesis. To utilize the knowledge of the underlying neurophysiological processes of natural movements, the concept of muscle synergy has been applied in prosthesis control and proved to be of great potential recently. For a muscle-synergy-based myoelectric system, the variation of muscle contraction force is also a confounding factor. This study evaluates the robustness of muscle synergies under a variant force level for forearm movements. Six channels of forearm surface EMG were recorded from six healthy subjects when they performed 4 movements (hand open, hand close, wrist flexion, and wrist extension) using low, moderate, and high force, respectively. Muscle synergies were extracted from the EMG using the alternating nonnegativity constrained least squares and active set (NNLS) algorithm. Three analytic strategies were adopted to examine whether muscle synergies were conserved under different force levels. Our results consistently showed that there exists fixed, robust muscle synergies across force levels. This outcome would provide valuable insights to the implementation of muscle-synergy-based assistive technology for the upper extremity.
引用
收藏
页码:3306 / 3309
页数:4
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