Publication:
An Overview of Classification of Electrooculography (EOG) Signals by Machine Learning Methods

dc.contributor.authorOdabas, Mehmet Serhat
dc.contributor.authorSuiçmez, Alihan
dc.contributor.authorTepe, Cengiz
dc.date.accessioned2025-12-10T23:21:12Z
dc.date.issued2022
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-tempOndokuz Mayıs Üniversitesi,Kastamonu Üniversitesi,Ondokuz Mayıs Üniversitesien_US
dc.description.abstractThe distribution of the studies conducted between 2011-2021 in the fields of (Electrooculography) EOG and eye movements, EOG and wheelchair, EOG and eye angle, EOG and sleep state, EOG and mood estimation and EOG and game application was determined according to years, and the most cited studies were examined and presented. The study areas are listed as Eye Movement Classification, Wheelchair, Sleep state, Eye Angle, Mood State and Game Applications from the most to the least number of articles. When we examine in terms of the number of citations, they are listed as Sleeping state, Eye Movement Classification, Wheelchair, Eye Angle, Mood State and Game Applications, from the most to the least. In these studies, it has been tried to make the lives of people who have become disabled in various ways better by using the brain-computer interface with machine learning.en_US
dc.identifier.doi10.29109/gujsc.1130972
dc.identifier.endpage338en_US
dc.identifier.issn2147-9526
dc.identifier.issue2en_US
dc.identifier.startpage330en_US
dc.identifier.trdizinid532960
dc.identifier.urihttps://doi.org/10.29109/gujsc.1130972
dc.identifier.urihttps://search.trdizin.gov.tr/en/yayin/detay/532960/an-overview-of-classification-of-electrooculography-eog-signals-by-machine-learning-methods
dc.identifier.urihttps://hdl.handle.net/20.500.12712/35374
dc.identifier.volume10en_US
dc.language.isoenen_US
dc.relation.ispartofGazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknolojien_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBilgisayar Bilimlerien_US
dc.subjectTeori ve Metotlaren_US
dc.subjectBilgisayar Bilimlerien_US
dc.subjectYapay Zekaen_US
dc.titleAn Overview of Classification of Electrooculography (EOG) Signals by Machine Learning Methodsen_US
dc.typeArticleen_US
dspace.entity.typePublication

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