Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/5170
Title: Detection of the Effects of Environmental Condition on Attention/Memory Using EEG Signals
Authors: Arinc, A.
Akbuğday, Burak
Akbugday, S.P.
Akan, Aydın
Keywords: attention
cognitive performance
electroencephalogram
machine learning
noise
working memory
Machine learning
Signal processing
Attention
Cognitive performance
Electroencephalogram signals
Environmental conditions
Machine-learning
N-back task
Noise
Noise levels
Subbands
Working memory
Electroencephalography
Publisher: Institute of Electrical and Electronics Engineers Inc.
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.
Description: 2023 Medical Technologies Congress, TIPTEKNO 2023 -- 10 November 2023 through 12 November 2023 -- 195703
URI: https://doi.org/10.1109/TIPTEKNO59875.2023.10359237
https://hdl.handle.net/20.500.14365/5170
ISBN: 9798350328967
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 full item record



CORE Recommender

Page view(s)

84
checked on Aug 19, 2024

Download(s)

2
checked on Aug 19, 2024

Google ScholarTM

Check




Altmetric


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