Feature Selection of Emg Signal Based on ReliefF Algorithm and Genetic Algorithm

Abstract

Abstract: Abstract： 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.

Key words: Key words： electromyography (EMG) signal, ReliefF algorithm, genetic algorithm(GA), feature selection

HE Tao,HU Jie,XIA Peng,GU Chaochen. Feature Selection of Emg Signal Based on ReliefF Algorithm and Genetic Algorithm[J]. Journal of Shanghai Jiaotong University, 2016, 50(02): 204-208.

References

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