Resonance based Respiratory Sound Decomposition Aiming at Localization of Crackles in Noisy Measurements

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dc.authoridUlukaya, Sezer/0000-0003-0473-7547
dc.authoridSerbes, Gorkem/0000-0003-4591-7368
dc.authorwosidKahya, Yasemin P/Q-1766-2015
dc.authorwosidUlukaya, Sezer/HJY-5331-2023
dc.authorwosidSerbes, Gorkem/AAZ-8822-2020
dc.authorwosidUlukaya, Sezer/N-9772-2015
dc.contributor.authorUlukaya, Sezer
dc.contributor.authorSerbes, Gorkem
dc.contributor.authorKahya, Yasemin P.
dc.date.accessioned2024-06-12T11:20:13Z
dc.date.available2024-06-12T11:20:13Z
dc.date.issued2016
dc.departmentTrakya Üniversitesien_US
dc.description38th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC) -- AUG 16-20, 2016 -- Orlando, FLen_US
dc.description.abstractIn this work, resonance based decomposition of lung sounds that aims to separate wheeze, crackle and vesicular sounds into three individual channels while automatically localizing crackles for both synthetic and real data is presented. Previous works focus on stationary-non stationary discrimination to separate crackles and vesicular sounds disregarding wheezes which are stationary as compared to crackles. However, wheeze sounds include important cues about the underlying pathology. Using two different threshold methods and synthetic sound generation scenarios in the presence of wheezes, resonance based decomposition performs 89.5 % crackle localization recall rate for white Gaussian noise and 98.6 % crackle localization recall rate for healthy vesicular sound treated as noise at low signal-to-noise ratios. Besides, an adaptive threshold determination which is independent from the channel at which it will be applied is used and is found to be robust to noise.en_US
dc.description.sponsorshipIEEE Engn Med & Biol Socen_US
dc.description.sponsorshipBogazici University [16A02D2]; Turkish Scientific Technical Research Council (TUBITAK) [2211]en_US
dc.description.sponsorshipThis work was supported by Bogazici University Research Fund under grant number 16A02D2. The work of S. Ulukaya is supported by the Ph.D. scholarship (2211) from Turkish Scientific Technical Research Council (TUBITAK).en_US
dc.identifier.endpage3691en_US
dc.identifier.issn1557-170X
dc.identifier.pmid28269094en_US
dc.identifier.scopus2-s2.0-85009091816en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage3688en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14551/25491
dc.identifier.wosWOS:000399823504011en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2016 38th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (Embc)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectVesicular Soundsen_US
dc.subjectSeparationen_US
dc.subjectTransformen_US
dc.subjectFilteren_US
dc.titleResonance based Respiratory Sound Decomposition Aiming at Localization of Crackles in Noisy Measurementsen_US
dc.typeConference Objecten_US

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