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DC Field | Value | Language |
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dc.contributor.author | Tsipouras, M.G., | en |
dc.contributor.author | Goletsis, Y., | en |
dc.contributor.author | Fotiadis, D.I. | en |
dc.date.accessioned | 2015-11-24T17:05:19Z | - |
dc.date.available | 2015-11-24T17:05:19Z | - |
dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/11299 | - |
dc.rights | Default Licence | - |
dc.title | A method for arrhythmic episode classification in ECGs using fuzzy logic and Markov models | en |
heal.type | journalArticle | - |
heal.type.en | Journal article | en |
heal.type.el | Άρθρο Περιοδικού | el |
heal.language | en | - |
heal.access | campus | - |
heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Οικονομικών και Κοινωνικών Επιστημών. Τμήμα Οικονομικών Επιστημών | el |
heal.publicationDate | 2004 | - |
heal.abstract | A merhod for arrhythmic episode classification using only the RR-interval signal is presented. The merhod is based on f u m logic and Markov models, while Classification is performed for nine categories of cardiac rhythms. A two-stage classifier is applied. In the first stage, a fuuy system clussiQies the episode using the mean value and standard deviaiion of the KR-intervals. In the second, the RR-interval signal is transformed to character sequences, which are classified by Markov models. Two representation techniques are used for the extraction of the characrer sequences: symbolic dynamics and one bused on the ER-interval length. The classification of an episode is achieved combining the outcomes of the two stages. The MIT-BIH arrhythmia database is used for the evaluation of the proposed method. The obtained results indicate high perlformance (accuracy 73%) in arrhythmic episode classijicafion. | en |
heal.journalName | Computers in Cardiology | en |
heal.journalType | peer reviewed | - |
heal.fullTextAvailability | TRUE | - |
Appears in Collections: | Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) - ΟΕ |
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goletsis-2004-a method for.pdf | 585.41 kB | Adobe PDF | View/Open Request a copy |
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