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EMG signal filtering based on Empirical Mode Decomposition

2006; Elsevier BV; Volume: 1; Issue: 1 Linguagem: Inglês

10.1016/j.bspc.2006.03.003

1746-8108

Adriano de Oliveira Andrade, Slawomir J. Nasuto, Peter Kyberd, Catherine M. Sweeney‐Reed, F.R. Van Kanijn,

Fault Detection and Control Systems

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.