Fetal ECG Extraction from Maternal Abdominal ECG Using Neural Network
DOI: 10.4236/jsea.2009.25043   PDF    HTML     10,083 Downloads   20,860 Views   Citations


FECG (Fetal ECG) signal contains potentially precise information that could assist clinicians in making more appro-priate and timely decisions during pregnancy and labor. The extraction and detection of the FECG signal from com-posite maternal abdominal signals with powerful and advance methodologies is becoming a very important requirement in fetal monitoring. The purpose of this paper is to illustrate the developed algorithms on FECG signal extraction from the abdominal ECG signal using Neural Network approach to provide efficient and effective ways of separating and understanding the FECG signal and its nature. The FECG signal was isolated from the abdominal signal by neural network approach with different learning constant value and momentum as well so that acceptable signal can be con-sidered. According to the output it can be said that the algorithm is working satisfactory on high learning rate and low momentum value. The method appears to be exceedingly robust, correctly isolate the FECG signal from abdominal ECG.

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M. HASAN, M. IBRAHIMY and M. REAZ, "Fetal ECG Extraction from Maternal Abdominal ECG Using Neural Network," Journal of Software Engineering and Applications, Vol. 2 No. 5, 2009, pp. 330-334. doi: 10.4236/jsea.2009.25043.

Conflicts of Interest

The authors declare no conflicts of interest.


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