Muscle Synergy and Musculoskeletal Model-Based Continuous Multi-Dimensional Estimation of Wrist and Hand Motions
Muscle Synergy and Musculoskeletal Model-Based Continuous Multi-Dimensional Estimation of Wrist and Hand Motions
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DOI：
10.1155/2020/5451219
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发表时间：
2020-01-28
影响因子：
--
通讯作者：
Koike, Yasuharu
中科院分区：
文献类型：
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作者：
Kim, Yeongdae;Stapornchaisit, Sorawit;Koike, Yasuharu
在这项研究中，七通道肌电图信号为基础的二维腕关节运动估计与无手柄运动进行。使用基于协同的线性回归模型和肌肉骨骼模型对肌电图信号进行了分析;随后将其与单一和组合的腕关节运动和握力进行了比较。使用手腕运动和抓握试验中的每一个作为训练集，基于协同的线性回归模型在二维手腕运动估计中表现出统计学显著的性能，Pearson相关系数（r）值为0.7891 +/- 0.0844，而肌肉骨骼模型的r值为0.7608 +/- 0.1037。对握力的估计产生0.8463 +/- 0.0503 r值，手腕运动范围的归一化均方根误差为0.2559 +/- 0.1397。当需要假肢、虚拟界面和康复中的基于肌电图的多维输入信号时，可以考虑这种连续的手腕和手柄估计。
In this study, seven-channel electromyography signal-based two-dimensional wrist joint movement estimation with and without handgrip motions was carried out. Electromyography signals were analyzed using the synergy-based linear regression model and musculoskeletal model; they were subsequently compared with respect to single and combined wrist joint movements and handgrip. Using each one of wrist motion and grip trial as a training set, the synergy-based linear regression model exhibited a statistically significant performance with 0.7891 +/- 0.0844 Pearson correlation coefficient (r) value in two-dimensional wrist motion estimation compared with 0.7608 +/- 0.1037 r value of the musculoskeletal model. Estimates on the grip force produced 0.8463 +/- 0.0503 r value with 0.2559 +/- 0.1397 normalized root-mean-square error of the wrist motion range. This continuous wrist and handgrip estimation can be considered when electromyography-based multi-dimensional input signals in the prosthesis, virtual interface, and rehabilitation are needed.