Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
558166 | Biomedical Signal Processing and Control | 2006 | 12 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Adriano O. Andrade, Slawomir Nasuto, Peter Kyberd, Catherine M. Sweeney-Reed, F.R. Van Kanijn,