北京生物醫(yī)學(xué)工程

基于三級(jí)濾波器的表面肌電信號(hào)降噪處理

Surface Electromyography Denoising Method Based on Three-Level Filter

作者：雷培源楊基海陳香

單位：中國科學(xué)技術(shù)大學(xué)電子科學(xué)與技術(shù)系（合肥230027）

關(guān)鍵詞：信號(hào)降噪；經(jīng)驗(yàn)?zāi)B(tài)分解；肌電分解

分類號(hào)：

出版年·卷·期（頁碼）：2011·30·1（62-66）

摘要：

表面肌電信號(hào)(surface electromyography, sEMG)是一種非平穩(wěn)微弱信號(hào)，而它的低信噪比是造成對(duì)其進(jìn)行分解十分困難的主要原因之一。本文針對(duì)sEMG信號(hào)的噪聲特點(diǎn)，提出基于經(jīng)驗(yàn)?zāi)B(tài)分解(empirical mode decomposition, EMD)的三級(jí)濾波器技術(shù)來對(duì)sEMG信號(hào)進(jìn)行預(yù)處理，即采用頻譜插值法去除工頻干擾，采用形態(tài)學(xué)運(yùn)算去除基線漂移，采用經(jīng)驗(yàn)?zāi)B(tài)分解去除白噪聲。實(shí)驗(yàn)結(jié)果表明，本文所提出的方法不僅能夠提高sEMG信號(hào)的信噪比，也能有效地保留運(yùn)動(dòng)單位動(dòng)作電位(motor unit action potential, MUAP)的波形信息，這將有利于對(duì)MUAP的識(shí)別從而提高對(duì)sEMG信號(hào)的分解準(zhǔn)確率。

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.

參考文獻(xiàn)：

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