Hand gesture recognition model based on surface EMG

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

doi:10.1117/12.2674601

23 May 2023 Hand gesture recognition model based on surface EMG

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

Proceedings Volume 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022); 126043R (2023) https://doi.org/10.1117/12.2674601
Event: 2nd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 2022, Guangzhou, China

Abstract

Four channels of surface EMG signals were collected from six gesture movements, and their time-domain and time-frequency domain features were extracted. Principal component analysis is used to reduce the dimension of features. For the dimension-reduced features, the decision tree is used to build a gesture recognition model. The experimental results show that the overall accuracy of the model for classifying six kinds of actions is more than 97%, which has good application value.

Citation Download Citation

Fan Chen, Fuhua Huang, Yuanyuan Yan, Ye Liu, Junzi Zhang, and Xiaoqi Zhang "Hand gesture recognition model based on surface EMG", Proc. SPIE 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 126043R (23 May 2023); https://doi.org/10.1117/12.2674601

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