吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (增刊1): 69-73.

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Pattern recognition of human arm motion based on neural network ensemble method

CHEN Wan-zhong, SUN Bao-feng, GAO Ren-jie, LEI Jun   

  1. College of Communication Engineering, Jilin University, Changchun 130022, China
  • Received:2012-05-16 Published:2013-06-01

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Abstract:

Neural network ensemble (NNE) was applied to the pattern recognition of human arm motion with sEMG signal's analyzing.The feature vectors of sEMG were extracted with wavelet packet decomposition,then a NNE model was generated using Bagging algorithm and BP neural network was used as sub neural network.The output of NNE was achieved by relative majority voting decision method.Finally,recognition experiments were done with sEMG signals gathered from four different hand movements,and the results reveal that NNE can increase the correct recognition rates significantly comparing with single neural network,proving the validity and feasibility of using NNE in the field of human arm motion recognition.

Key words: neural network ensemble, surface electromyography (sEMG), wavelet packet decomposition, pattern recognition

CLC Number: 

  • TP183

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