A Novel Feature Reduction Method for Real-Time EMG Pattern Recognition System
Yang, Peipei1; Xing, Kexin2; Huang, Jian3; Wang, Yongji3
2013-05
会议名称Chinese Control and Decision Conference (CCDC)
会议录名称2013 25th Chinese Control and Decision Conference (CCDC)
会议日期2013-5-25
会议地点Guiyang, China
摘要This paper proposes a novel feature reduction approach for real-time electromyogram (EMG) pattern recognition. This study extracts time and frequency information by wavelet packet transform (WPT) coefficients and uses the node energy as the feature to overcome the translation-invariant property of WPT. Then the non-parametric discriminant analysis (NDA) is used for feature reduction. Because of some inherent properties of the packet node energy, the within-class scatter matrix is usually singular in this approach, which makes feature project unavailable. To solve this problem, a recursive algorithm is proposed to discard some feature components that lead to singularity and contain relatively less discriminant information. Finally, the support vector machine (SVM) is used as the classifier and gives the recognition result. The corresponding pattern of the action could be recognized in a millisecond (ms). The experimental results show that the proposed method has strong robustness and good real-time performance.
关键词Emg Real-time Pattern Recognition Wavelet Packet Non-parametric Weighted Feature Extraction Svm
DOI10.1109/CCDC.2013.6561165
引用统计
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/12502
专题模式识别国家重点实验室_模式分析与学习
通讯作者Yang, Peipei
作者单位1.Institute of Automation, Chinese Academy of Science
2.College of Information Engineering, Zhejiang University of Technology
3.Huazhong University of Science and Technology
推荐引用方式
GB/T 7714
Yang, Peipei,Xing, Kexin,Huang, Jian,et al. A Novel Feature Reduction Method for Real-Time EMG Pattern Recognition System[C],2013.
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