A Biomedical System Based on Artificial Neural Network and Principal Component Analysis for Diagnosis of the Heart Valve Diseases

Basit Öğe Kaydı
dc.contributor.authorUguz, Harun
dc.date.accessioned2020-03-26T18:23:27Z
dc.date.available2020-03-26T18:23:27Z
dc.date.issued2012
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractListening via stethoscope is a primary method, being used by physicians for distinguishing normally and abnormal cardiac systems. Listening to the voices, coming from the cardiac valves via stethoscope, upon the flow of the blood running in the heart, physicians examine whether there is any abnormality with regard to the heart. However, listening via stethoscope has got a number of limitations, for interpreting different heart sounds depends on hearing ability, experience, and respective skill of the physician. 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 was mainly comprised of three stages, namely as being feature extraction, dimension reduction, and classification. At feature extraction stage, applying Discrete Fourier Transform (DFT) and Burg autoregressive (AR) spectrum analysis method, features, representing heart sounds in frequency domain, were obtained. Obtained features were reduced in lower dimensions via Principal Component Analysis (PCA), being used as a dimension reduction technique. Heart sounds were classified by having the features applied as input to Artificial Neural Network (ANN). Classification results have shown that, dimension reduction, being conducted via PCA, has got positive effects on the classification of the heart sounds.en_US
dc.description.sponsorshipSelcuk UniversitySelcuk Universityen_US
dc.description.sponsorshipThis study has been supported by Scientific Research Project of Selcuk University.en_US
dc.identifier.doi10.1007/s10916-010-9446-7en_US
dc.identifier.endpage72en_US
dc.identifier.issn0148-5598en_US
dc.identifier.issue1en_US
dc.identifier.pmid20703748en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage61en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s10916-010-9446-7
dc.identifier.urihttps://hdl.handle.net/20.500.12395/27655
dc.identifier.volume36en_US
dc.identifier.wosWOS:000303823600007en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherSPRINGERen_US
dc.relation.ispartofJOURNAL OF MEDICAL SYSTEMSen_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 fourier transformen_US
dc.subjectBurg autoregressive methoden_US
dc.subjectArtificial neural networken_US
dc.subjectPrincipal component analysisen_US
dc.titleA Biomedical System Based on Artificial Neural Network and Principal Component Analysis for Diagnosis of the Heart Valve Diseasesen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
PubMed İndeksli Yayın Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu