Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14365/5850
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sipahioglu, E. | - |
dc.contributor.author | Akbugday, B. | - |
dc.contributor.author | Akbugday, S.P. | - |
dc.contributor.author | Akan, A. | - |
dc.date.accessioned | 2025-01-25T17:06:40Z | - |
dc.date.available | 2025-01-25T17:06:40Z | - |
dc.date.issued | 2024 | - |
dc.identifier.isbn | 979-833152981-9 | - |
dc.identifier.uri | https://doi.org/10.1109/TIPTEKNO63488.2024.10755381 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14365/5850 | - |
dc.description.abstract | The 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.sponsorship | Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, TÜBİTAK, (1199B472338877); Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, TÜBİTAK | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.ispartof | TIPTEKNO 2024 - Medical Technologies Congress, Proceedings -- 2024 Medical Technologies Congress, TIPTEKNO 2024 -- 10 October 2024 through 12 October 2024 -- Mugla -- 204315 | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Eeg | en_US |
dc.subject | Environment | en_US |
dc.subject | Machine Learning | en_US |
dc.subject | N-Back Task | en_US |
dc.subject | Noise | en_US |
dc.subject | Ppg | en_US |
dc.subject | Working Memory | en_US |
dc.title | Investigating the Effect of Noise Levels on Mental Tasks Using Artificial Intelligence | en_US |
dc.type | Conference Object | en_US |
dc.identifier.doi | 10.1109/TIPTEKNO63488.2024.10755381 | - |
dc.identifier.scopus | 2-s2.0-85212708588 | - |
dc.department | İzmir Ekonomi Üniversitesi | en_US |
dc.authorscopusid | 59481780300 | - |
dc.authorscopusid | 57211987353 | - |
dc.authorscopusid | 57215310544 | - |
dc.authorscopusid | 35617283100 | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | N/A | - |
dc.identifier.wosquality | N/A | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.openairetype | Conference Object | - |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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