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The Signal Processing and Identification of Upper Limb Motion Based on sEMG

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Abstract

The system principle diagram of Robot based on Surface electromyography signal (sEMG) is presented in this paper. The hardware of the control system and the mode of training and the spectacle of virtual reality are designed. The sEMG can reflect nerves and muscles’ motion to a certain degree and has great practical value in clinical medical as well as in the medical rehabilitation. The flow chart of the sEMG signal processing and feature extraction methods based on the original sEMG are introduced in the paper. Fourier transform is used on the basis of stationary random signal, time–frequency analysis method are used to overcome the nonlinear characteristics of sEMG signal. The back propagation network is used to realize the type of action recognition based on sEMG. It is important to establish a quantitative relationship between the model and the joint angle sEMG signal. The research will be helpful to develop the EMG signals into the actual application of the medical robot.

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Acknowledgements

The research was supplied by the Key Laboratory of High-efficiency and Clean Mechanical Manufacture at Shandong University, Ministry of Education, Jinan, China. At the same time, it was also supplied by the Key Laboratory of computer application at Shandong Women University. The corresponding author of the paper are Zhou Yiqi (School of Mechanical Engineering, Shandong University) and Li Ying (School of Information Technology, Shandong Women University).

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Authors and Affiliations

  1. School of Mechanical Engineering, Shandong University, Jinan, China

    Changsong Li & Yiqi Zhou

  2. School of Information Technology, Shandong Women University, Jinan, China

    Ying Li

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  1. Changsong Li
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  2. Yiqi Zhou
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  3. Ying Li
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Correspondence to Yiqi Zhou.

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Li, C., Zhou, Y. & Li, Y. The Signal Processing and Identification of Upper Limb Motion Based on sEMG. Wireless Pers Commun 103, 887–896 (2018). https://doi.org/10.1007/s11277-018-5485-z

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  • DOI: https://doi.org/10.1007/s11277-018-5485-z

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