Feature selection of Emg signal based on ReliefF algorithm and genetic algorithm

被引：0

作者：

He T. ^{[1
]}

Hu J. ^{[1
]}

Xia P. ^{[1
]}

Gu C. ^{[1
]}

机构：

[1] School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai

来源：

Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University | 2016年 / 50卷 / 02期

关键词：

Electromyography (EMG) signal; Feature selection; Genetic algorithm(GA); ReliefF algorithm;

D O I：

10.16183/j.cnki.jsjtu.2016.02.008

中图分类号：

学科分类号：

摘要：

To address the high dimension of signal characteristics and low operation efficiency of electromyography (EMG), an algorithm for feather selection was proposed based on ReliefF feature evaluation and the genetic algorithm. The characteristics of the signal was analyzed, the features of the EMG signal with wavelet transform were extracted, the weight of each feature was assessed using the ReliefF algorithm, and the feature subset which has a obvious influence upon classification result was selected. Then the best feature subset for the classification results was screened out by using the genetic algorithm. Besides, the operation time and classification results of the ReliefF-GA-Wrapper algorithm were compared with those of the global search. The result shows that the proposed algorithm not only guarantees a good classification result but also improves the operational efficiency. © 2016, Editorial Board of Journal of Shanghai Jiao Tong University. All right reserved.

引用

页码：204 / 208

页数：4

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