Feature selection for surface electromyography signal using cultural algorithm
基于文化算法的表面肌电信号特征选择

To improve classification accuracy of the surface electromyography(sEMG)-based prosthesis,this paper proposed a new way to select feature based on cultural algorithm(CA) and used here.It tested its classification performance with linear discrimina analysis(LDA).The method used surface differential electrodes to acquire four EMG signals from human body’s upper limbs.Ten healthy subjects participated in the experiment of classification of eight hand motion’s sEMG signals.Test results show that the algorithm can get a good result of classification.Compared with the standard genetic algorithm(GA),it has better search performance.