An improved method for sEMG segmentation

An improved method of continuous action's sEMG automatic segmentation is presented in this paper. The maximum value and the integral value of local area are regarded as the distinguishing standard for start or stop action area, and search area adjusted dynamicly can speed up the sEMG segmentation. The experiment results show that, the methods which are proposed in the paper can achieve sEMG's automatic segmentation, which consider less natural factors of action individual. The segmentation accuracy is higher, the effect is better, the time that is spent in the segmentation is shorter than the former method, and it provides more convenient for subsequent signal processing.