Performance comparison of genetic algorithm and principal component analysis methods for ECG signal extraction
by S. Balambigai, R. Asokan
International Journal of Healthcare Technology and Management (IJHTM), Vol. 12, No. 5/6, 2011

Abstract: Electrocardiogram (ECG) signal analysis is a technique to diagnose the cardiac diseases. But, the desired electrocardiogram signals are often corrupted by baseline interference, power line interference and electromyogram. Here, a method is proposed to extract ECG from noisy signals based on Singular Value Decomposition (SVD) and Genetic Algorithm. The advantage of this method compared to conventional methods like adaptive filtering, neural networks is that it does not require any prior knowledge of the signals. It is found that the signal to noise ratio improvement is nearly double when compared to neural network methods.

Online publication date: Sat, 28-Mar-2015

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