Performance Comparison Research of the FECG Signal Separation Based on the BSS Algorithm

Abstract

Fetal Electrocardiogram (FECG) is a weak signal through placing the electrodes upon the maternal belly surface to indirectly monitor, which contains all the forms of jamming signal. So, how to separate the FECG from the strong background interference has important value of clinical application. Independent Component Analysis (ICA) is a kind of developed new Blind Source Separation (BSS) technology in recent years. This study adopted ICA method to the extraction of FECG and carried out the blind signal separation by using the Fast ICA algorithm and natural gradient algorithm in the FECG separation research. The experimental results shown that the two kind of algorithm can obtain the good separation result. But because the natural gradient algorithm can achieve FECG online separation and separation effect is better than Fast ICA algorithm, therefore, the natural gradient algorithm is a better way to used in FECG separation. And it will help to monitor the congenital heart disease, neonatal arrhythmia, intrauterine fetal retardation and other diseases, which has very important test application value.

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Cite this paper

@inproceedings{Wen2012PerformanceCR, title={Performance Comparison Research of the FECG Signal Separation Based on the BSS Algorithm}, author={Xinling Wen}, year={2012} }