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An Efficient Approach for Fetal ECG Extraction

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Abdullah Mohammed Kaleem, Rajendra D. Kokate

Abdullah Mohammed Kaleem and Rajendra D Kokate. An Efficient Approach for Fetal ECG Extraction. International Journal of Computer Applications 182(33):1-5, December 2018. BibTeX

	author = {Abdullah Mohammed Kaleem and Rajendra D. Kokate},
	title = {An Efficient Approach for Fetal ECG Extraction},
	journal = {International Journal of Computer Applications},
	issue_date = {December 2018},
	volume = {182},
	number = {33},
	month = {Dec},
	year = {2018},
	issn = {0975-8887},
	pages = {1-5},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2018918258},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Fetal ECG contains precise knowledge that may aid doctor in creating well-suited choices throughout pregnancy and labor. Authentic FECG signal is still extraordinarily complicated and very contaminated by outer disturbances. Hence extraction of clean fetal ECG is extraordinarily crucial for fetal surveillance. This is often accomplished by putting electrodes on mother’s abdomen. Anyway it is tainted with varied sources of noise. This paper compares LMS adaptive filter for FECG extraction with neural network based adaptive filter. Real fetal ECG database was used. Experimental results validated superiority of later scheme in terms of SNR and MSE.


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Fetal ECG, abdominal ECG, adaptive filter, neural network