Integration of type-2 fuzzy clustering and wavelet transform in a neural network based ECG classifier

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dc.contributor.authorOzbay, Yuksel
dc.contributor.authorCeylan, Rahime
dc.contributor.authorKarlik, Bekir
dc.date.accessioned2020-03-26T18:14:57Z
dc.date.available2020-03-26T18:14:57Z
dc.date.issued2011
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThis paper presents a new automated diagnostic system to classification of electrocardiogram (ECG) arrhythmias. The diagnostic system is executed using type-2 fuzzy c-means clustering (T2FCM) algorithm, wavelet transform (WT) and neural network. Method of combining T2FCM and WT is used to improve performance of neural network. We aimed high accuracy rate to classification of ECG beats and constituted the automated diagnostic system to improve of classifier's performance. Ten types of ECG beats selected from MIT-BIH database were used to train the system. Then, this system was tested by the ECG signals of patients. The classification accuracy of the proposed classifier, type-2 fuzzy clustering wavelet neural network (T2FCWNN), is compared with the structures formed by type-1 FCM and WT. Process of T2FCWNN architecture is realized on three stages. First stage is formed the new training set obtained by selection of the best segments for each arrhythmia class using T2FCM. Second stage is feature extraction by WT on the new training set. Third stage is classification of the extracted features using neural network. The research showed that accuracy rate was found as 99% using this system. (C) 2010 Elsevier Ltd. All rights reserved.en_US
dc.description.sponsorshipCoordinatorship of Selcuk UniversitySelcuk University [07101021]en_US
dc.description.sponsorshipThis work is supported by the Coordinatorship of Selcuk University's Scientific Research Projects under Project No. 07101021.en_US
dc.identifier.doi10.1016/j.eswa.2010.07.118en_US
dc.identifier.endpage1010en_US
dc.identifier.issn0957-4174en_US
dc.identifier.issn1873-6793en_US
dc.identifier.issue1en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1004en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2010.07.118
dc.identifier.urihttps://hdl.handle.net/20.500.12395/26568
dc.identifier.volume38en_US
dc.identifier.wosWOS:000282607800114en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPERGAMON-ELSEVIER SCIENCE LTDen_US
dc.relation.ispartofEXPERT SYSTEMS WITH APPLICATIONSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectType-2 fuzzy c-means clusteringen_US
dc.subjectWavelet transformen_US
dc.subjectECGen_US
dc.subjectArrhythmiaen_US
dc.subjectNeural networken_US
dc.subjectClassificationen_US
dc.titleIntegration of type-2 fuzzy clustering and wavelet transform in a neural network based ECG classifieren_US
dc.typeArticleen_US

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