Performance comparison of MeRMaId-ICA and Np-ICA in composite abdominal electrocardiogram separation

Autor:	Anisha M, Benisha M, Kumar S S
Rok vydání:	2019
Předmět:	Signal-to-interference ratio Correlation coefficient Computer science Noise (signal processing) business.industry Biomedical Engineering Pattern recognition Mutual information Signal Blind signal separation Independent component analysis Signal-to-noise ratio Artificial intelligence business
Zdroj:	International Journal of Biomedical Engineering and Technology. 30:195
ISSN:	1752-6426 1752-6418
DOI:	10.1504/ijbet.2019.10022264
Popis:	Blind source separation strives to disintegrate a multivariate composite non-invasive abdominal electrocardiogram signal into independent non-Gaussian signals such as maternal and foetal electrocardiograms. This paper proffers two separation algorithms especially for foetal electrocardiogram (FECG) extraction as it has a great role in diagnosing the foetal heart deformities namely minimum Renyi's mutual information called MeRMaId algorithm and non-parametric independent component analysis (Np-ICA) algorithm. Both the algorithms are experimentally evaluated on synthetic and real abdominal data. Performance juxtaposition of these two algorithms is done by scrutinising the signal to noise ratio at assorted noise levels and signal to interference ratio at assorted amplitude levels, and computing correlation coefficient (ρ) of the original and the estimated maternal and foetal electrocardiograms.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::076f4ff1edea5feff11ed198aad9b683 https://doi.org/10.1504/ijbet.2019.10022264 Zobrazit plný text záznamu