基于三级滤波器的表面肌电信号降噪处理

Surface Electromyography Denoising Method Based on Three-Level Filter

表面肌电信号(surface electromyography,sEMG)是一种非平稳微弱信号,而它的低信噪比是造成对其进行分解十分困难的主要原因之一。本文针对sEMG信号的噪声特点,提出基于经验模态分解(empirical mode decomposition,EMD)的三级滤波器技术来对sEMG信号进行预处理,即采用频谱插值法去除工频干扰,采用形态学运算去除基线漂移,采用经验模态分解去除白噪声。实验结果表明,本文所提出的方法不仅能够提高sEMG信号的信噪比,也能有效地保留运动单位动作电位(motor unit action potential,MUAP)的波形信息,这将有利于对MUAP的识别从而提高对sEMG信号的分解准确率。

Surface electromyography （sEMG） is a non-stationary weak signal. It is very difficult to decompose sEMG signal, one of the main reasons is the sEMG signal with low signal-to-noise ratio（SNR）. In this paper, a method, which is named three-level filtering technology based on empirical mode decomposition （EMD） , is presented for sEMG signal preprocessing. Three filtering algorithms are adopted according to the noise characteristics of sEMG signal, including spectrum interpolation for the removal of interference from power line, morphological filter for the removal of baseline drift and empirical mode decomposition for the removal of white noise. The experimental results demonstrate that the proposed three-level filtering technology can not only improve the SNR of sEMG signal but also effectively reserve the main waveform features of MUAP. This will facilitate the identification of the MUAP and sequentially to improve the accuracy of sEMG signal decomposition.