EMG signal filtering based on Empirical Mode Decomposition

Andrade, A. O., Nasuto, S. ORCID: https://orcid.org/0000-0001-9414-9049, Kyberd, P., Sweeney-Reed, C. M. and Van Kanijn, F. R. (2006) EMG signal filtering based on Empirical Mode Decomposition. Biomedical Signal Processing and Control, 1 (1). pp. 44-55. ISSN 1746-8094 doi: 10.1016/j.bspc.2006.03.003

Abstract/Summary

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 my 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. (c) 2006 Elsevier Ltd. All rights reserved.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/15112
Item Type	Article
Refereed	Yes
Divisions	Life Sciences > School of Biological Sciences > Department of Bio-Engineering
Uncontrolled Keywords	Electromyography, Empirical Mode Decomposition, Wavelets, Adaptive, filters
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