Classification of Parkinson's Disease Using Dynamic Time Warping

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dc.authoridUlukaya, Sezer/0000-0003-0473-7547
dc.authoridKurt, İlke/0000-0001-5911-9282;
dc.authorwosidUlukaya, Sezer/HJY-5331-2023
dc.authorwosidUlukaya, Sezer/N-9772-2015
dc.authorwosidKurt, İlke/AAG-6476-2019
dc.authorwosiderdem, oğuzhan/AAG-6229-2019
dc.contributor.authorKurt, Ilke
dc.contributor.authorUlukaya, Sezer
dc.contributor.authorErdem, Oguzhan
dc.date.accessioned2024-06-12T10:59:54Z
dc.date.available2024-06-12T10:59:54Z
dc.date.issued2019
dc.departmentTrakya Üniversitesien_US
dc.description27th Telecommunications Forum (TELFOR) -- NOV 26-27, 2019 -- Belgrade, SERBIAen_US
dc.description.abstractDeteriorations in handwriting or in basic shape sketching are one of the most referenced symptoms for early diagnosis of Parkinson's disease (PD). For this reason, the design of a fair, trustworthy and efficacious Computer-aided Diagnosis (CAD) model has supportive importance for the early diagnosis of PD. In this study we investigate the effectiveness of Dynamic Time Warping (DTW) algorithm, which is applied to Archimedean spiral drawings of patients with PD and healthy controls (HC), on PD and healthy subject classification problem. Leave-one-subject-out (LOSO) cross validation scheme is used while training and testing in support vector machine (SVM) and k-nearest neighbors (k-NN) classifiers with various parameters. The accuracy results of %94.44 (%95.83) and %97.52 (%94.44) are achieved by k-NN and SVM classifiers respectively for static (dynamic) spiral test.en_US
dc.description.sponsorshipTelecommunicat Soc,Univ Belgrade, Sch Elect Engn,IEEE Serbia & Montenegro COM Chapter,TELEKOM SRBIJA a d,Minist Trade Tourism & Telecommunicat,VLATACOM d o o,Nokia,Ericsson,Cisco,IRITEL a d,Maksnet Telekomunikacije,Minist Educ Sci & Technol Dev,Javno Preduzece Posta Srbije,Republ Agcy Elect Commun Serbia,Roaming Networks,TERI Engn,VIP Mobile,TELENOR,IEEE Serbia & Montenegro Sect,IEEE Reg 8en_US
dc.identifier.endpage336en_US
dc.identifier.isbn978-1-7281-4789-5
dc.identifier.scopus2-s2.0-85079326273en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage333en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14551/20617
dc.identifier.wosWOS:000568618700080en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2019 27th Telecommunications Forum (Telfor 2019)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDTWen_US
dc.subjectHandwriting Analysisen_US
dc.subjectMachine Learningen_US
dc.subjectParkinson's Diseaseen_US
dc.subjectSpiral Drawingsen_US
dc.subjectFeaturesen_US
dc.titleClassification of Parkinson's Disease Using Dynamic Time Warpingen_US
dc.typeConference Objecten_US

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