Block entropy analysis of heart rate variability signals

Karamanos, K; Nikolopoulos, S; Hizanidis, K; Manis, G; Alexandridi, A; Nikolareas, S

dc.contributor.author	Karamanos, K	en
dc.contributor.author	Nikolopoulos, S	en
dc.contributor.author	Hizanidis, K	en
dc.contributor.author	Manis, G	en
dc.contributor.author	Alexandridi, A	en
dc.contributor.author	Nikolareas, S	en
dc.date.accessioned	2014-03-01T01:23:40Z
dc.date.available	2014-03-01T01:23:40Z
dc.date.issued	2006	en
dc.identifier.issn	0218-1274	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17081
dc.subject	Block entropies	en
dc.subject	Electrocardiograms	en
dc.subject	Heart rate variability	en
dc.subject	Lumping	en
dc.subject	Symbolic dynamics	en
dc.subject.classification	Mathematics, Interdisciplinary Applications	en
dc.subject.classification	Multidisciplinary Sciences	en
dc.subject.other	Correlation methods	en
dc.subject.other	Disease control	en
dc.subject.other	Electrocardiography	en
dc.subject.other	Entropy	en
dc.subject.other	Block entropies	en
dc.subject.other	Coronary Artery Disease (CAD)	en
dc.subject.other	Heat Rate Variability (HRV) data	en
dc.subject.other	Lumping	en
dc.subject.other	Symbolic dynamics	en
dc.subject.other	Cardiovascular system	en
dc.title	Block entropy analysis of heart rate variability signals	en
heal.type	journalArticle	en
heal.identifier.primary	10.1142/S0218127406015933	en
heal.identifier.secondary	http://dx.doi.org/10.1142/S0218127406015933	en
heal.language	English	en
heal.publicationDate	2006	en
heal.abstract	In this paper we present a novel approach to the analysis of Heat Rate Variability (HRV) data, by coarse-graining analysis using the estimation of Block Entropies with the technique of lumping. HRV time series are generated from long recordings of Electrocardiograms (ECGs) and are then filtered in order to produce a coarse-grained symbolic dynamics. Block Entropy analysis is applied to these dynamics in order to examine its coarse-grained statistics. Our data set is comprised of two subsets, one of healthy subjects and another of Coronary Artery Disease (CAD) patients. It is found that Entropy analysis provides a quick and efficient tool for the differentiation of these series according to subject category. Healthy subjects provided more complex statistics compared to patients; specifically, the healthy data files provided higher values of block Entropies compared to patient ones. We also compare these results with the Correlation Dimension Estimation in order to establish coherency. We believe that this analysis may provide a useful statistical method towards the better understanding of the human cardiac system. © World Scientific Publishing Company.	en
heal.publisher	WORLD SCIENTIFIC PUBL CO PTE LTD	en
heal.journalName	International Journal of Bifurcation and Chaos	en
dc.identifier.doi	10.1142/S0218127406015933	en
dc.identifier.isi	ISI:000240860400017	en
dc.identifier.volume	16	en
dc.identifier.issue	7	en
dc.identifier.spage	2093	en
dc.identifier.epage	2101	en