Feature selection in HRV analysis of young and elderly subjects

dc.contributor.author	Tripoliti, E.	en
dc.contributor.author	Manis, G.	en
dc.date.accessioned	2015-12-11T10:42:15Z
dc.date.available	2015-12-11T10:42:15Z
dc.identifier.uri	https://olympias.lib.uoi.gr/jspui/handle/123456789/26573
dc.rights	Default License
dc.subject	Engineering
dc.title	Feature selection in HRV analysis of young and elderly subjects	en
heal.abstract	In this paper we apply several feature selection algorithms on features extracted from heartbeat timeseries recorded from young and elderly healthy subjects. We investi gate the results in an attempt to see which of those features are selected from the majority of the algorithms and start a discus sion on the results. All commonly used HRV analysis methods are investigated starting from simple statistical methods to non-linear ones. The results show that for the specific dataset most algorithms agree on the features they consider more significant.	en
heal.access	campus
heal.bibliographicCitation	Βιβλιογραφία: σ. 519	en
heal.bookName	Feature Selection in HRV Analysis of Young and Elderly Subjects	en
heal.fullTextAvailability	true
heal.generalDescription	516-519 σ.	el
heal.language	en
heal.publicationDate	2012
heal.publisher	A. Jobbágy and R. Magjarevic
heal.recordProvider	Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Η/Υ & Πληροφορικής	el
heal.type	bookChapter
heal.type.el	Κεφάλαιο βιβλίου	el
heal.type.en	Book chapter	en

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