Respiratory Sound Classification Using Perceptul Linear Prediction Features for Healthy - Pathological Diagnosis

dc.authoridUlukaya, Sezer/0000-0003-0473-7547;
dc.authorwosidUlukaya, Sezer/N-9772-2015
dc.authorwosidUlukaya, Sezer/HJY-5331-2023
dc.authorwosidKahya, Yasemin P/Q-1766-2015
dc.contributor.authorUlukaya, Sezer
dc.contributor.authorKahya, Yasemin P.
dc.date.accessioned2024-06-12T11:20:52Z
dc.date.available2024-06-12T11:20:52Z
dc.date.issued2014
dc.departmentTrakya Üniversitesien_US
dc.description18th National Biomedical Engineering Meeting (BIYOMUT) -- OCT 16-17, 2014 -- Istanbul, TURKEYen_US
dc.description.abstractThis study proposes a new model and feature extraction method for the classification of multi-channel respiratory sound data with the final aim of building a diagnosis aid tool for the medical doctor. Fourteen-channel data are processed separately and combined at feature level and fed to the support vector machines with radial basis kernel. Healthy-pathological subject based binary classification is employed where the recall rates for the healthy class and pathological class are 95 percent and 80 percent, respectively. The minimum precision rate is 80 percent. The method, when supported by additional features (adventitious sound frequency, type, etc.), may be employed in clinical practice as an aiding decision maker.en_US
dc.identifier.doi10.1109/BIYOMUT.2014.7026343
dc.identifier.isbn978-1-4799-7572-3
dc.identifier.scopus2-s2.0-84988246894en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/BIYOMUT.2014.7026343
dc.identifier.urihttps://hdl.handle.net/20.500.14551/25807
dc.identifier.wosWOS:000381577500011en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherIEEEen_US
dc.relation.ispartof2014 18th National Biomedical Engineering Meeting (Biyomut)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subject[No Keywords]en_US
dc.titleRespiratory Sound Classification Using Perceptul Linear Prediction Features for Healthy - Pathological Diagnosisen_US
dc.typeConference Objecten_US

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