Performance comparison of MeRMaId-ICA and Np-ICA in composite abdominal electrocardiogram separation. (28th June 2019)

• Record Type: Journal Article
• Authors: Anisha, M.; Kumar, S.S.; Benisha, M.
• Is Part Of: International journal of biomedical engineering and technology. Volume 30:Number 3(2019)
• Page Start: 195
• Page End: 211
• Publication Date: 2019-06-28
• Subjects: minimum Renyi's mutual information -- non-parametric independent component analysis -- maternal electrocardiogram -- foetal electrocardiogram -- FECG; Biomedical engineering -- Periodicals; 610.28
• Languages: English
• ISSNs: 1752-6418

Abstract

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.