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| SEMG Movement Pattern Recognition of Hand Based on Correlation Analysis and SVM |
| Xi Xu-gang Li Zhong-ning Luo Zhi-zeng |
| Robotics Research Institute, Hangzhou Dianzi University, Hangzhou 310018, China |
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Abstract In order to extract effectively the feature of SEMG signal, an improved method of feature extraction based on correlation analysis is proposed. Firstly, the paper decreases the noise included in two channel SEMG signals using spatial correlation filtering. Secondly, the paper analyzes SEMG signal after de-noising with 4-scale wavelet transformation and extract wavelet coefficient of the main fringe by arithmetic of correlation analysis. A 6-dimension eigenvector which is constructed with sum of squares of the wavelet coefficient is inputted SVM. The result shows that four movements (wrist spreads, wrist bends, hand extension, hand grasps) are successfully identified by the method of SVM combined with the eigenvector which is constructed at the condition of correlation analysis and wavelet transformation. The more precise classified results can be get than neural network sorter with this method.
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Received: 03 April 2007
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Corresponding Authors:
Xi Xu-gang
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2008, Vol. 30 
