Determination of Window Size and Sliding Interval for EMG Signals by Using Genetic Algorithm

The selection of window size and sliding interval are one of the important problems encountered in Electromyography (EMG) signal processing. However, there exist a few methods to determine the window size and sliding interval for EMG signal classification problems. In this paper, a new method is proposed to optimize the window size and sliding interval for EMG signals by using Genetic Algorithm. Experimental results on a EMG data set show that the proposed method improve the performance of a traditional classifier in terms of classification accuracy.