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

dc.contributor.authorSUİÇMEZ, Alihan
dc.contributor.authorTEPE, Cengiz
dc.contributor.authorODABAS, Mehmet Serhat
dc.date.accessioned2026-01-06T06:05:20Z
dc.date.issued2022-06-30
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.
dc.description.urihttps://doi.org/10.29109/gujsc.1130972
dc.description.urihttps://doaj.org/article/7c8805ae0d7645c99fe078866d3a6c89
dc.description.urihttps://dergipark.org.tr/tr/pub/gujsc/issue/69964/1130972
dc.identifier.doi10.29109/gujsc.1130972
dc.identifier.eissn2147-9526
dc.identifier.endpage338
dc.identifier.openairedoi_dedup___::eea41996a4fef60add82c03d190e95c5
dc.identifier.orcid0000-0002-0502-6547
dc.identifier.orcid0000-0003-4065-5207
dc.identifier.orcid0000-0002-1863-7566
dc.identifier.startpage330
dc.identifier.urihttps://hdl.handle.net/20.500.12597/43893
dc.identifier.volume10
dc.publisherGazi Universitesi Fen Bilimleri Dergisi Part C: Tasarim ve Teknoloji
dc.relation.ispartofGazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji
dc.rightsOPEN
dc.subjectScience (General)
dc.subjectScience
dc.subjectQ
dc.subjectMühendislik
dc.subjectEngineering (General). Civil engineering (General)
dc.subjecteog
dc.subjectQ1-390
dc.subjectEngineering
dc.subjectmachine learning
dc.subjectEOG
dc.subjectElectrooculography
dc.subjectMachine Learning
dc.subjectelectrooculography
dc.subjectTA1-2040
dc.titleAn Overview of Classification of Electrooculography (EOG) Signals by Machine Learning Methods
dc.typeArticle
dspace.entity.typePublication
local.api.response{"authors":[{"fullName":"Alihan SUİÇMEZ","name":"Alihan","surname":"SUİÇMEZ","rank":1,"pid":{"id":{"scheme":"orcid_pending","value":"0000-0002-0502-6547"},"provenance":null}},{"fullName":"Cengiz TEPE","name":"Cengiz","surname":"TEPE","rank":2,"pid":{"id":{"scheme":"orcid","value":"0000-0003-4065-5207"},"provenance":null}},{"fullName":"Mehmet Serhat ODABAS","name":"Mehmet Serhat","surname":"ODABAS","rank":3,"pid":{"id":{"scheme":"orcid_pending","value":"0000-0002-1863-7566"},"provenance":null}}],"openAccessColor":"gold","publiclyFunded":false,"type":"publication","language":{"code":"und","label":"Undetermined"},"countries":null,"subjects":[{"subject":{"scheme":"keyword","value":"Science (General)"},"provenance":null},{"subject":{"scheme":"keyword","value":"Science"},"provenance":null},{"subject":{"scheme":"keyword","value":"Q"},"provenance":null},{"subject":{"scheme":"keyword","value":"Mühendislik"},"provenance":null},{"subject":{"scheme":"keyword","value":"Engineering (General). Civil engineering (General)"},"provenance":null},{"subject":{"scheme":"FOS","value":"01 natural sciences"},"provenance":null},{"subject":{"scheme":"FOS","value":"0104 chemical sciences"},"provenance":null},{"subject":{"scheme":"keyword","value":"eog"},"provenance":null},{"subject":{"scheme":"keyword","value":"Q1-390"},"provenance":null},{"subject":{"scheme":"keyword","value":"Engineering"},"provenance":null},{"subject":{"scheme":"keyword","value":"machine learning"},"provenance":null},{"subject":{"scheme":"keyword","value":"EOG;Electrooculography;Machine Learning"},"provenance":null},{"subject":{"scheme":"keyword","value":"electrooculography"},"provenance":null},{"subject":{"scheme":"keyword","value":"TA1-2040"},"provenance":null}],"mainTitle":"An Overview of Classification of Electrooculography (EOG) Signals by Machine Learning Methods","subTitle":null,"descriptions":["<jats:p xml:lang=\"en\">The 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.</jats:p>"],"publicationDate":"2022-06-30","publisher":"Gazi Universitesi Fen Bilimleri Dergisi Part C: Tasarim ve Teknoloji","embargoEndDate":null,"sources":["Crossref","Gazi Üniversitesi Fen Bilimleri Dergisi, Vol 10, Iss 2, Pp 330-338 (2022)","Volume: 10, Issue: 2 330-338","2147-9526","Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji","Gazi University Journal of Science Part C: Design and Technology"],"formats":["application/pdf"],"contributors":null,"coverages":null,"bestAccessRight":{"code":"c_abf2","label":"OPEN","scheme":"http://vocabularies.coar-repositories.org/documentation/access_rights/"},"container":{"name":"Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji","issnPrinted":null,"issnOnline":"2147-9526","issnLinking":null,"ep":"338","iss":null,"sp":"330","vol":"10","edition":null,"conferencePlace":null,"conferenceDate":null},"documentationUrls":null,"codeRepositoryUrl":null,"programmingLanguage":null,"contactPeople":null,"contactGroups":null,"tools":null,"size":null,"version":null,"geoLocations":null,"id":"doi_dedup___::eea41996a4fef60add82c03d190e95c5","originalIds":["10.29109/gujsc.1130972","50|doiboost____|eea41996a4fef60add82c03d190e95c5","50|doajarticles::bd191d8bd886e109eef2290b0437730f","oai:doaj.org/article:7c8805ae0d7645c99fe078866d3a6c89","oai:dergipark.org.tr:article/1130972","50|tubitakulakb::08100c7071ce357ae90a15b3065a721c"],"pids":[{"scheme":"doi","value":"10.29109/gujsc.1130972"}],"dateOfCollection":null,"lastUpdateTimeStamp":null,"indicators":{"citationImpact":{"citationCount":3,"influence":2.7078255e-9,"popularity":4.199307e-9,"impulse":3,"citationClass":"C5","influenceClass":"C5","impulseClass":"C5","popularityClass":"C4"}},"instances":[{"pids":[{"scheme":"doi","value":"10.29109/gujsc.1130972"}],"type":"Article","urls":["https://doi.org/10.29109/gujsc.1130972"],"publicationDate":"2022-06-30","refereed":"peerReviewed"},{"alternateIdentifiers":[{"scheme":"doi","value":"10.29109/gujsc.1130972"}],"type":"Article","urls":["https://doaj.org/article/7c8805ae0d7645c99fe078866d3a6c89"],"publicationDate":"2022-06-01","refereed":"nonPeerReviewed"},{"alternateIdentifiers":[{"scheme":"doi","value":"10.29109/gujsc.1130972"}],"type":"Article","urls":["https://dergipark.org.tr/tr/pub/gujsc/issue/69964/1130972"],"publicationDate":"2022-06-14","refereed":"nonPeerReviewed"}],"isGreen":false,"isInDiamondJournal":false}
local.import.sourceOpenAire

Dosyalar

Koleksiyonlar