A Robust and Non-invasive Fetal Electrocardiogram Extraction Algorithm in a Semi-Blind Way

Yalan YE  Zhi-Lin ZHANG  Jia CHEN  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E91-A   No.3   pp.916-920
Publication Date: 2008/03/01
Online ISSN: 1745-1337
DOI: 10.1093/ietfec/e91-a.3.916
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Neural Networks and Bioengineering
Keyword: 
neural network,  independent component analysis (ICA),  blind source separation (BSS),  blind source extraction (BSE),  fetal electrocardiogram (FECG),  

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Summary: 
Fetal electrocardiogram (FECG) extraction is of vital importance in biomedical signal processing. A promising approach is blind source extraction (BSE) emerging from the neural network fields, which is generally implemented in a semi-blind way. In this paper, we propose a robust extraction algorithm that can extract the clear FECG as the first extracted signal. The algorithm exploits the fact that the FECG signal's kurtosis value lies in a specific range, while the kurtosis values of other unwanted signals do not belong to this range. Moreover, the algorithm is very robust to outliers and its robustness is theoretically analyzed and is confirmed by simulation. In addition, the algorithm can work well in some adverse situations when the kurtosis values of some source signals are very close to each other. The above reasons mean that the algorithm is an appealing method which obtains an accurate and reliable FECG.