A knowledge-based technique for automated detection of ischaemic episodes in long duration electrocardiograms

dc.contributor.authorPapaloukas, C.en
dc.contributor.authorFotiadis, D. I.en
dc.contributor.authorLiavas, A. P.en
dc.contributor.authorLikas, A.en
dc.contributor.authorMichalis, L. K.en
dc.date.accessioned2015-11-24T17:32:33Z
dc.date.available2015-11-24T17:32:33Z
dc.identifier.issn0140-0118-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/13747
dc.rightsDefault Licence-
dc.subjectischaemic episodes detectionen
dc.subjectknowledge-based methoden
dc.subjectecg noise handlingen
dc.subjectartificial neural-networken
dc.subjectst-segment analysisen
dc.subjectmyocardial-infarctionen
dc.subjectecg analysisen
dc.subjectischemiaen
dc.subjectrecoveryen
dc.subjectsystemen
dc.titleA knowledge-based technique for automated detection of ischaemic episodes in long duration electrocardiogramsen
heal.abstractA novel method for the detection of ischaemic episodes in long duration ECGs is proposed. It includes noise handling, feature extraction, rule-based beat classification, sliding window classification and ischaemic episode identification, all integrated in a four-stage procedure. It can be executed in real time and is able to provide explanations for the diagnostic decisions obtained The method was tested on the ESC ST-T database and high scores were obtained for both sensitivity and positive predictive accuracy (93.8% and 78.5% respectively using aggregate gross statistics, and 90.7% and 80.7% using aggregate average statistics).en
heal.accesscampus-
heal.fullTextAvailabilityTRUE-
heal.identifier.secondary<Go to ISI>://000166793200016-
heal.identifier.secondaryhttp://www.springerlink.com/content/5434012392701650/fulltext.pdf-
heal.journalNameMed Biol Eng Computen
heal.journalTypepeer reviewed-
heal.languageen-
heal.publicationDate2001-
heal.publisherSpringer-Verlagen
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Επιστήμης Υλικώνel
heal.typejournalArticle-
heal.type.elΆρθρο Περιοδικούel
heal.type.enJournal articleen

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