Iranian Journal of Biomedical Engineering (IJBME)
نشریه علمی مهندسی پزشکی زیستی

Applying The Blind Separation Of Correlated Sources For FECG Extraction Based On The Second Order Statistics

Document Type : Full Research Paper

Author

Masoud Reza Aghabozorgi Sahaf

Assistant Professor, Communication Department, Electrical and Computer Engineering School, Yazd University

10.22041/ijbme.2008.13549
Abstract
The extraction of the fetal electrocardiogram (FECG) from the skin electrode signals recorded of the mother's body is a problem of concern to signal processing. Blind signal separation (BSS) technique that separates some signals from their combinations without acknowledgments about transmission channel, is a fundamental method for solving this problem. The most proposed BSS algorithm for separation of fetal electrocardiogram (FECG) and mother electrocardiogram (MECG) relies on the independence of these signals (ICA). This paper introduces a novel technique for the cases that signals are correlated with each other, i.e. considering a real assumption.  The  method uses Wold decomposition principle for extracting the desired and proper information from the predictable part of the measured data, and exploits approaches based on the second-order statistics to estimate source signals. Simulation results are showed the effectiveness of the method for separation of electrocardiogram signals. 

Keywords

FECG extraction
Blind source separation
Independent component analysis
Wold decomposition
Second order statistics

Subjects

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Iranian Journal of Biomedical Engineering (IJBME)
Volume 1, Issue 4 - Serial Number 4
Spring 2007
Pages 301-310

  • Receive Date 03 July 2015

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