多通道表面肌电信号降噪与去混迭研究

通过数据采集装置同时采集多路表面肌电信号(sEMG)时,信号之间往往存在相互混迭的现象。为了得到有效的sEMG,提出了一种基于二代小波变换和独立分量分析(ICA)相结合的降噪与去混迭方法。先利用二代小波变换对sEMG降噪再利用改进的FastICA算法对降噪后的信号进行ICA分离,最后通过互相关系数验证去混迭效果。实验结果表明,所提方法能够有效降低噪声并去除相邻通道间产生的混迭。

A Study of Multi-channel sEMG De-noising and Aliasing Removal

There is an aliasing between the multi-channels of Surface Electromyographys (sEMG) when they are collected by a data acquisition device. The sEMG will inevitably be affected by noise due to the influence of acquisition equipment and the environment. In order to obtain unmixed sEMG, a new method is proposed. The method that combined by second generation wavelet transform and independent component analysis (ICA): makes use of second generation wavelet transform to reduce noise in the sEMG, then, takes a ICA signal separation on sEMG by the improved FastICA algorithm. Finally, the paper introduces correlation coefficient to verify anti-aliasing effect. The experimental results indicate that this method is an effective way to de-noise and separate the mutual mixed sEMG.