sEMG Signal classification for the motion pattern of intelligent bionic artificial limb

Authors:
Yang Li;Yantao Tian;Wanzhong Chen
Affiliations:
School of Communication Engineering, Jilin University, Changchun;School of Communication Engineering, Jilin University, Changchun and Key Laboratory of Bionic Engineering, Ministry of Education Jilin University;School of Communication Engineering, Jilin University, Changchun
Venue:
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part I
Year:
2011

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Abstract

Surface EMG (sEMG) signal classification based on the motion pattern plays an important role in control system design of intelligent bionic artificial limb. The key problems and the corresponding solutions of sEMG signal classification, which consist of recognition rate, algorithm complexity, robustness and real-time characteristic, were summarized in this paper. By comparing with the performance of practical application, the research directions for the future work are pointed out at last.