INDEPENDENT COMPONENT ANALYSIS AND DISCRETE WAVELET TRANSFORM FOR ARTIFACT REMOVAL IN BIOMEDICAL SIGNAL PROCESSING
- 1 Department of Civil Engineering, Environment, Energy and Materials, Mediterranea University of Reggio Calabria, Via Graziella Feo di Vito, I-89122 Reggio Calabria, Italy
Recent works have shown that artifact removal in biomedical signals can be performed by using Discrete Wavelet Transform (DWT) or Independent Component Analysis (ICA). It results often very difficult to remove some artifacts because they could be superimposed on the recordings and they could corrupt the signals in the frequency domain. The two conditions could compromise the performance of both DWT and ICA methods. In this study we show that if the two methods are jointly implemented, it is possible to improve the performances for the artifact rejection procedure. We discuss in detail the new method and we also show how this method provides advantages with respect to DWT of ICA procedure. Finally, we tested the new approach on real data.
Copyright: © 2014 Salvatore Calcagno, Fabio La Foresta and Mario Versaci. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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- Artifact Removal
- Discrete Wavelet Transform
- Independent Component Analysis
- Neural Networks
- Surface EMG