Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/5850
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dc.contributor.authorSipahioglu, E.-
dc.contributor.authorAkbugday, B.-
dc.contributor.authorAkbugday, S.P.-
dc.contributor.authorAkan, A.-
dc.date.accessioned2025-01-25T17:06:40Z-
dc.date.available2025-01-25T17:06:40Z-
dc.date.issued2024-
dc.identifier.isbn979-833152981-9-
dc.identifier.urihttps://doi.org/10.1109/TIPTEKNO63488.2024.10755381-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/5850-
dc.description.abstractThe impact of stress on daily life has been a subject of interest in the last decades. The utilization of numerous electrical and electronic devices as well as increased land and air transportation densities constantly create noise which is a significant contributor to stress. In this study, the relationship between environmental noise, cognitive workload, and stress is investigated. Electroencephalogram (EEG) and photoplethysmogram (PPG) signals of 30 volunteers were recorded simultaneously while performing a 2-back task with different background noise levels. Features were then extracted from the processed signals to be classified with various machine learning algorithms. Results show that medium noise levels result in increased accuracy for the 2-back task which indicates keeping the noise levels at an acceptable level would be better for work and learning environments. © 2024 IEEE.en_US
dc.description.sponsorshipTürkiye Bilimsel ve Teknolojik Araştırma Kurumu, TÜBİTAK, (1199B472338877); Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, TÜBİTAKen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofTIPTEKNO 2024 - Medical Technologies Congress, Proceedings -- 2024 Medical Technologies Congress, TIPTEKNO 2024 -- 10 October 2024 through 12 October 2024 -- Mugla -- 204315en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectEegen_US
dc.subjectEnvironmenten_US
dc.subjectMachine Learningen_US
dc.subjectN-Back Tasken_US
dc.subjectNoiseen_US
dc.subjectPpgen_US
dc.subjectWorking Memoryen_US
dc.titleInvestigating the Effect of Noise Levels on Mental Tasks Using Artificial Intelligenceen_US
dc.typeConference Objecten_US
dc.identifier.doi10.1109/TIPTEKNO63488.2024.10755381-
dc.identifier.scopus2-s2.0-85212708588-
dc.departmentİzmir Ekonomi Üniversitesien_US
dc.authorscopusid59481780300-
dc.authorscopusid57211987353-
dc.authorscopusid57215310544-
dc.authorscopusid35617283100-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityN/A-
dc.identifier.wosqualityN/A-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypeConference Object-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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