Robust Method for Separation of Noisy Biomedical Signals

Abstract:

Biomedical signals are a rich source of information about physiological processes, but they are often contaminated by noise. In order to separate biomedical signals from mixtures effectually, we propose a novel blind source extraction method via independent component analysis (ICA). The robustness with respect to noise of this method lies in two-fold: on the one hand, the method does not lead to biassed estimates and, on the other hand, it minimizes the amount of signal and noise interference on the estimated sources. Preliminary results tested with ECG signals have demonstrated that the proposed method may be promising for blindly separating biomedical signals in the presence of noise and further decompose the mixed signals into subcomponents.

• Periodical: Applied Mechanics and Materials (Volumes 26-28)
• Pages: 5-8
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.26-28.5
• Online since: June 2010
• Authors: Yong Jian Zhao, Bio Qiang Liu
• Keywords: Additive Noise, Biomedical Signal, Blind Signal Separation, ECG, ICA, Least Square (LS), Regression Analysis

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DOI: 10.1109/97.763148