EMG signal filtering based on Empirical Mode Decomposition

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• 作者：Adriano O. Andrade ; Slawomir Nasuto ; Peter Kyberd ; Catherine M. Sweeney-Reed ; F.R. Van Kanijn
• 关键词：Electromyography ; Empirical Mode Decomposition ; Wavelets ; Adaptive filters
• 刊名：Biomedical Signal Processing and Control
• 出版年：2006
• 出版时间：January 2006
• 年：2006
• 卷：1
• 期：1
• 页码：44-55
• 全文大小：1326 K

文摘

This paper introduces a procedure for filtering electromyographic (EMG) signals. Its key element is the Empirical Mode Decomposition, a novel digital signal processing technique that can decompose any time-series into a set of functions designated as intrinsic mode functions. The procedure for EMG signal filtering is compared to a related approach based on the wavelet transform. Results obtained from the analysis of synthetic and experimental EMG signals show that our method can be successfully and easily applied in practice to attenuation of background activity in EMG signals.