Differential Diagnosis of Asthma and COPD Based on Multivariate Pulmonary Sounds Analysis

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dc.authoridSaraclar, Murat/0000-0002-7435-8510|Sen, Ipek/0000-0001-8471-4083|Kahya, Yasemin P/0000-0001-5137-1205
dc.authorwosidSaraclar, Murat/E-8640-2010
dc.contributor.authorSen, Ipek
dc.contributor.authorSaraclar, Murat
dc.contributor.authorKahya, Yasemin P.
dc.date.accessioned2024-07-18T20:47:27Z
dc.date.available2024-07-18T20:47:27Z
dc.date.issued2021
dc.departmentİstanbul Bilgi Üniversitesien_US
dc.description.abstractObjective: Asthma and chronic obstructive pulmonary disease (COPD) can be confused in clinical diagnosis due to overlapping symptoms. The purpose of this study is to develop a method based on multivariate pulmonary sounds analysis for differential diagnosis of the two diseases. Methods: The recorded 14-channel pulmonary sound data are mathematically modeled using multivariate (or, vector) autoregressive (VAR) model, and the model parameters are fed to the classifier. Separate classifiers are assumed for each of the six sub-phases of flow cycle, namely, early/mid/late inspiration and expiration, and the six decisions are combined to reach the final decision. Parameter classification is performed in the Bayesian framework with the assumption of Gaussian mixture model (GMM) for the likelihoods, and the six sub-phase decisions are combined by voting, where the weights are learned by a linear support vector machine (SVM) classifier. Fifty subjects are incorporated in the study, 30 being diagnosed with asthma and 20 with COPD. Results: The highest accuracy of the classifier is 98 percent, corresponding to correct classification rates of 100 and 95 percent for asthma and COPD, respectively. The prominent sub-phase to differentiate between the two diseases is found to be mid-inspiration. Conclusion: The methodology proves to be promising in terms of asthma-COPD differentiation based on acoustic information. The results also reveal that the six sub-phases are not equally pertinent in the differentiation. Significance: Pulmonary sounds analysis may be a complementary tool in clinical practice for differential diagnosis of asthma and COPD, especially in the absence of reliable spirometric testing.en_US
dc.description.sponsorshipBogazici University Research Fund [09A203D]en_US
dc.description.sponsorshipThis work was supported by Bogazici University Research Fund under Project 09A203D.en_US
dc.identifier.doi10.1109/TBME.2021.3049288
dc.identifier.endpage1610en_US
dc.identifier.issn0018-9294
dc.identifier.issn1558-2531
dc.identifier.issue5en_US
dc.identifier.pmid33400647en_US
dc.identifier.scopus2-s2.0-85099243459en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1601en_US
dc.identifier.urihttps://doi.org/10.1109/TBME.2021.3049288
dc.identifier.urihttps://hdl.handle.net/11411/7788
dc.identifier.volume68en_US
dc.identifier.wosWOS:000641967300015en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherIEEE-Inst Electrical Electronics Engineers Incen_US
dc.relation.ispartofIeee Transactions on Biomedical Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectLungen_US
dc.subjectDiseasesen_US
dc.subjectMathematical Modelen_US
dc.subjectSupport Vector Machinesen_US
dc.subjectStethoscopeen_US
dc.subjectReactive Poweren_US
dc.subjectPathologyen_US
dc.subjectAsthmaen_US
dc.subjectCopden_US
dc.subjectDiagnostic Classificationen_US
dc.subjectDifferential Diagnosisen_US
dc.subjectPulmonary Soundsen_US
dc.subjectGmmen_US
dc.subjectSvmen_US
dc.subjectVar Modelen_US
dc.subjectRespiratory Soundsen_US
dc.subjectClassificationen_US
dc.subjectCracklesen_US
dc.subjectDiseaseen_US
dc.subjectModelen_US
dc.subjectSvmen_US
dc.titleDifferential Diagnosis of Asthma and COPD Based on Multivariate Pulmonary Sounds Analysisen_US
dc.typeArticleen_US

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