z-logo
open-access-imgOpen Access
Blind Maternal-Fetal ECG Separation Based on the Time-Scale Image TSI and SVD – ICA Methods
Author(s) -
Said Ziani,
Atman Jbari,
Larbi Bellarbi,
Yousef Farhaoui
Publication year - 2018
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2018.07.179
Subject(s) - computer science , blind signal separation , matlab , artificial intelligence , signal (programming language) , pattern recognition (psychology) , independent component analysis , singular value decomposition , speech recognition , channel (broadcasting) , telecommunications , programming language , operating system
Fetal heart monitoring yields vital information about the fetus health and can support medical decision making in critical situations. A compound signal is obtained noninvasively by placing electrodes on the abdomen area of the mother which contains maternal and fetal ECG signals contaminated by various other signals from body and externally induced noises. As a result, the basic problem is to extract the fECG signal from the mixture of mECG and fECG, where the interfering mECG is a much stronger. This problem has been addressed in several works, in this paper, we propose a novel blind-source separation method to extract fetal ECG when given only a single channel recording. Our approach is based on the wavelet theory and SVD-ICA methods. It is pointed out that the presented algorithm is validated by Matlab simulation and can be implemented on real time life by using embedded system such as DSP processor.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom