Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14365/5170
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Arinc, A. | - |
dc.contributor.author | Akbuğday, Burak | - |
dc.contributor.author | Akbugday, S.P. | - |
dc.contributor.author | Akan, Aydın | - |
dc.date.accessioned | 2024-02-24T13:39:03Z | - |
dc.date.available | 2024-02-24T13:39:03Z | - |
dc.date.issued | 2023 | - |
dc.identifier.isbn | 9798350328967 | - |
dc.identifier.uri | https://doi.org/10.1109/TIPTEKNO59875.2023.10359237 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14365/5170 | - |
dc.description | 2023 Medical Technologies Congress, TIPTEKNO 2023 -- 10 November 2023 through 12 November 2023 -- 195703 | en_US |
dc.description.abstract | Several 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.sponsorship | BAP2022-07 | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.ispartof | TIPTEKNO 2023 - Medical Technologies Congress, Proceedings | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | attention | en_US |
dc.subject | cognitive performance | en_US |
dc.subject | electroencephalogram | en_US |
dc.subject | machine learning | en_US |
dc.subject | noise | en_US |
dc.subject | working memory | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Signal processing | en_US |
dc.subject | Attention | en_US |
dc.subject | Cognitive performance | en_US |
dc.subject | Electroencephalogram signals | en_US |
dc.subject | Environmental conditions | en_US |
dc.subject | Machine-learning | en_US |
dc.subject | N-back task | en_US |
dc.subject | Noise | en_US |
dc.subject | Noise levels | en_US |
dc.subject | Subbands | en_US |
dc.subject | Working memory | en_US |
dc.subject | Electroencephalography | en_US |
dc.title | Detection of the Effects of Environmental Condition on Attention/Memory Using EEG Signals | en_US |
dc.type | Conference Object | en_US |
dc.identifier.doi | 10.1109/TIPTEKNO59875.2023.10359237 | - |
dc.identifier.scopus | 2-s2.0-85182732694 | en_US |
dc.department | İzmir Ekonomi Üniversitesi | en_US |
dc.authorscopusid | 58821732200 | - |
dc.authorscopusid | 57211987353 | - |
dc.authorscopusid | 58821521400 | - |
dc.authorscopusid | 35617283100 | - |
dc.institutionauthor | … | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | N/A | - |
dc.identifier.wosquality | N/A | - |
item.grantfulltext | reserved | - |
item.openairetype | Conference Object | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | With Fulltext | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | 05.06. Electrical and Electronics Engineering | - |
crisitem.author.dept | 05.06. Electrical and Electronics Engineering | - |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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File | Size | Format | |
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5170.pdf Restricted Access | 271.09 kB | Adobe PDF | View/Open Request a copy |
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