Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/5170
Full metadata record
DC FieldValueLanguage
dc.contributor.authorArinc, A.-
dc.contributor.authorAkbuğday, Burak-
dc.contributor.authorAkbugday, S.P.-
dc.contributor.authorAkan, Aydın-
dc.date.accessioned2024-02-24T13:39:03Z-
dc.date.available2024-02-24T13:39:03Z-
dc.date.issued2023-
dc.identifier.isbn9798350328967-
dc.identifier.urihttps://doi.org/10.1109/TIPTEKNO59875.2023.10359237-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/5170-
dc.description2023 Medical Technologies Congress, TIPTEKNO 2023 -- 10 November 2023 through 12 November 2023 -- 195703en_US
dc.description.abstractSeveral studies suggest that attention is affected by several factors in workplaces and classrooms such as noise levels. These studies are often conducted via surveys and statistical methods to assess the cognitive performances of individuals. In this study, the effect of environmental conditions on attention and memory is investigated using Electroencephalogram (EEG). EEG signals from 32 participants were recorded for three cases with different noise levels while they were performing an n-back task. Sub-band powers of the EEG signals were then extracted using the filtered signals and these features were then classified using several machine learning classifiers. Results indicate that increased noise levels have detrimental effects whereas calm environments have positive effects on attention and working memory. © 2023 IEEE.en_US
dc.description.sponsorshipBAP2022-07en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofTIPTEKNO 2023 - Medical Technologies Congress, Proceedingsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectattentionen_US
dc.subjectcognitive performanceen_US
dc.subjectelectroencephalogramen_US
dc.subjectmachine learningen_US
dc.subjectnoiseen_US
dc.subjectworking memoryen_US
dc.subjectMachine learningen_US
dc.subjectSignal processingen_US
dc.subjectAttentionen_US
dc.subjectCognitive performanceen_US
dc.subjectElectroencephalogram signalsen_US
dc.subjectEnvironmental conditionsen_US
dc.subjectMachine-learningen_US
dc.subjectN-back tasken_US
dc.subjectNoiseen_US
dc.subjectNoise levelsen_US
dc.subjectSubbandsen_US
dc.subjectWorking memoryen_US
dc.subjectElectroencephalographyen_US
dc.titleDetection of the Effects of Environmental Condition on Attention/Memory Using EEG Signalsen_US
dc.typeConference Objecten_US
dc.identifier.doi10.1109/TIPTEKNO59875.2023.10359237-
dc.identifier.scopus2-s2.0-85182732694en_US
dc.departmentİzmir Ekonomi Üniversitesien_US
dc.authorscopusid58821732200-
dc.authorscopusid57211987353-
dc.authorscopusid58821521400-
dc.authorscopusid35617283100-
dc.institutionauthor-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityN/A-
dc.identifier.wosqualityN/A-
item.grantfulltextreserved-
item.openairetypeConference Object-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
crisitem.author.dept05.06. Electrical and Electronics Engineering-
crisitem.author.dept05.06. Electrical and Electronics Engineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Files in This Item:
File SizeFormat 
5170.pdf
  Restricted Access
271.09 kBAdobe PDFView/Open    Request a copy
Show simple item record



CORE Recommender

Page view(s)

106
checked on Nov 18, 2024

Download(s)

4
checked on Nov 18, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.