Alzheimer's Disease Diagnosis Using Olfactory Stimulus Evoked Electroencephalography Signals

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dc.authoridOlcay, Bilal Orkan/0000-0003-3721-6756
dc.authorscopusid57190736569
dc.authorscopusid6701644598
dc.authorwosidOlcay, Bilal Orkan/AAJ-1750-2020
dc.contributor.authorOlcay, B. Orkan
dc.contributor.authorPehlivan, Murat
dc.date.accessioned2024-08-25T18:32:43Z
dc.date.available2024-08-25T18:32:43Z
dc.date.issued2023
dc.departmentEge Üniversitesien_US
dc.description31st IEEE Conference on Signal Processing and Communications Applications (SIU) -- JUL 05-08, 2023 -- Istanbul Tech Univ, Ayazaga Campus, Istanbul, TURKEYen_US
dc.description.abstractOlfactory loss is commonly recognized as one of the first symptoms of Alzheimer's disease, which makes it a potential biomarker for early diagnosis. However, psychophysical and electrophysiological tests, routinely used for diagnosis, are often not sufficient for detection of olfactory loss. In this study, chemosensory evoked electroencephalography (EEG) signals were characterized via brain-computer interface feature extraction methods to classify Alzheimer's patients and healthy individuals. Results showed that combining EEG features and University of Pennsylvania Smell Identification Test (UPSIT) scores commonly used for diagnosis of olfactory loss, achieved a conspicuous success rate of nearly 92% in diagnosis. The findings suggest that the proposed approach can be considered as a new strategy for early diagnosis of Alzheimer's diseaseen_US
dc.description.sponsorshipIEEE,TUBITAK BILGEM,Turkcellen_US
dc.identifier.doi10.1109/SIU59756.2023.10223913
dc.identifier.isbn979-8-3503-4355-7
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-85173480328en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/SIU59756.2023.10223913
dc.identifier.urihttps://hdl.handle.net/11454/100310
dc.identifier.wosWOS:001062571000146en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherIEEEen_US
dc.relation.ispartof2023 31st Signal Processing and Communications Applications Conference, Siuen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240825_Gen_US
dc.subjectChemosensory brain responsesen_US
dc.subjectElectroencephalographyen_US
dc.subjectBrain-computer interfacesen_US
dc.subjectAlzheimer's Diseaseen_US
dc.subjectSupport vector machineen_US
dc.titleAlzheimer's Disease Diagnosis Using Olfactory Stimulus Evoked Electroencephalography Signalsen_US
dc.typeConference Objecten_US

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