Adaptive neuro-fuzzy inference system for diagnosis of the heart valve diseases using wavelet transform with entropy

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dc.contributor.authorUguz, Harun
dc.date.accessioned2020-03-26T18:23:43Z
dc.date.available2020-03-26T18:23:43Z
dc.date.issued2012
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractListening via stethoscope is a preferential method, being used by physicians for distinguishing normal and abnormal cardiac systems. On the other hand, listening with stethoscope has a number of constraints. The interpretation of various heart sounds depends on physician's ability of hearing, experience, and skill. Such limitations may be reduced by developing biomedical-based decision support systems. In this study, a biomedical-based decision support system was developed for the classification of heart sound signals, obtained from 120 subjects with normal, pulmonary, and mitral stenosis heart valve diseases via stethoscope. Developed system comprises of three stages. In the first stage, for feature extraction, obtained heart sound signals were separated to its sub-bands using discrete wavelet transform (DWT). In the second stage, entropy of each sub-band was calculated using Shannon entropy algorithm to reduce the dimensionality of the feature vectors via DWT. In the third stage, the reduced features of three types of heart sound signals were used as input patterns of the adaptive neuro-fuzzy inference system (ANFIS) classifiers. Developed method reached 98.33% classification accuracy, and it was showed that purposed method is effective for detection of heart valve diseases.en_US
dc.description.sponsorshipScientific Research Project of Selcuk UniversitySelcuk University; Afyon Kocatepe University, Afyonkarahisar, TurkeyAfyon Kocatepe University [07.AFMYO.01]en_US
dc.description.sponsorshipThis study has been supported by Scientific Research Project of Selcuk University. Also, I thank, the Afyon Kocatepe University, Afyonkarahisar, Turkey for providing the heart sound data to me (Project No: 07.AFMYO.01).en_US
dc.identifier.doi10.1007/s00521-011-0610-xen_US
dc.identifier.endpage1628en_US
dc.identifier.issn0941-0643en_US
dc.identifier.issn1433-3058en_US
dc.identifier.issue7en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1617en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s00521-011-0610-x
dc.identifier.urihttps://hdl.handle.net/20.500.12395/27713
dc.identifier.volume21en_US
dc.identifier.wosWOS:000308825000013en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSPRINGER LONDON LTDen_US
dc.relation.ispartofNEURAL COMPUTING & APPLICATIONSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectHeart sounden_US
dc.subjectDiscrete wavelet transformen_US
dc.subjectAdaptive neuro-fuzzy inference systemen_US
dc.subjectEntropyen_US
dc.titleAdaptive neuro-fuzzy inference system for diagnosis of the heart valve diseases using wavelet transform with entropyen_US
dc.typeArticleen_US

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