Research Article Open Access

INDEPENDENT COMPONENT ANALYSIS AND DISCRETE WAVELET TRANSFORM FOR ARTIFACT REMOVAL IN BIOMEDICAL SIGNAL PROCESSING

Salvatore Calcagno1, Fabio La Foresta1 and Mario Versaci1
  • 1 Department of Civil Engineering, Environment, Energy and Materials, Mediterranea University of Reggio Calabria, Via Graziella Feo di Vito, I-89122 Reggio Calabria, Italy

Abstract

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.

American Journal of Applied Sciences
Volume 11 No. 1, 2014, 57-68

DOI: https://doi.org/10.3844/ajassp.2014.57.68

Submitted On: 4 October 2012 Published On: 27 November 2013

How to Cite: Calcagno, S., Foresta, F. L. & Versaci, M. (2014). INDEPENDENT COMPONENT ANALYSIS AND DISCRETE WAVELET TRANSFORM FOR ARTIFACT REMOVAL IN BIOMEDICAL SIGNAL PROCESSING. American Journal of Applied Sciences, 11(1), 57-68. https://doi.org/10.3844/ajassp.2014.57.68

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Keywords

  • Artifact Removal
  • Discrete Wavelet Transform
  • Independent Component Analysis
  • Neural Networks
  • Surface EMG