Hand motion perception prediction based on surface electromyography

Chen Fan; Fuhua Huang; Ming Jing; Xiaodong Zhang; Yuanyuan Yan; Ye Liu; Junzi Zhang; Xiaoqi Zhang

doi:10.1117/12.2675185

25 May 2023 Hand motion perception prediction based on surface electromyography

Chen Fan, Fuhua Huang, Ming Jing, Xiaodong Zhang, Yuanyuan Yan, Ye Liu, Junzi Zhang, Xiaoqi Zhang

Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 1263635 (2023) https://doi.org/10.1117/12.2675185
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China

Abstract

In order to solve the real-time control problem of hand rehabilitation exoskeleton robot, a motion angle decoding model was proposed based on surface EMG signal and synchronous motion angle value. The long short-term memory neural network was used to construct the hand motion angle decoding model. During recognition, EMG signal and synchronous angle signal are sent to the model for decoding, and the output of the model is the angle prediction value after 200ms. The experimental results show that the combination of motion angle signal and EMG signal can significantly improve the decoding ability of the model.

Citation Download Citation

Chen Fan, Fuhua Huang, Ming Jing, Xiaodong Zhang, Yuanyuan Yan, Ye Liu, Junzi Zhang, and Xiaoqi Zhang "Hand motion perception prediction based on surface electromyography", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 1263635 (25 May 2023); https://doi.org/10.1117/12.2675185

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