利用sEMG能量高斯分布特性提取动作信号的方法

摘要

Motion segment and extraction from continuous signals is the premise of surface electromyography (sEMG) analysis, For the problem that sEMG energy threshold required repeated manual testing to set, this the paper established a this mathematical model of continuous actions based on Gaussian sEMG energy curve, in which the energy threshold was set according to the distribution of Gaussian signal section, and differentiated the action signals from no-action signals combined with energy comparison method. The experiment results showed the method can achieve continuous repetitive action segmentation, and compared with manual segmentation of the same signal, has a higher degree of coincidence.%对于采集到的连续动作肌电信号，首先要进行动作信号的分割和提取，该文针对肌电能量阈值需要反复人工试验才能设置的问题，从sEMG信号能量高斯分布特性出发，建立了连续重复动作的数学模型，进而根据高斯分布的区间规律设定能量阈值，结合能量比较的方法实现了动作信号的有效分割和提取。实验表明，该方法可以实现连续重复动作的有效分割，并且与信号手工分段的结果相比，达到了较高的重合度。