Electroencephalogram (eeg) stress analysis on alpha/beta ratio and theta/beta ratio

This paper presents an analysis of stress feature using the power ratio of frequency bands including Alpha to Beta and Theta to Beta. In this study, electroencephalography (EEG) acquisition tool was utilized to collect brain signals from 40 subjects and objectively reflected stress features induced...

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Main Authors: Tee, Y. W., Mohd. Aris, S. A.
Format: Article
Published: Institute of Advanced Engineering and Science 2020
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Online Access:http://eprints.utm.my/id/eprint/87106/
http://www.dx.doi.org/10.11591/ijeecs.v17.i1.pp175-182
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spelling my.utm.871062020-10-31T12:23:30Z http://eprints.utm.my/id/eprint/87106/ Electroencephalogram (eeg) stress analysis on alpha/beta ratio and theta/beta ratio Tee, Y. W. Mohd. Aris, S. A. T Technology (General) This paper presents an analysis of stress feature using the power ratio of frequency bands including Alpha to Beta and Theta to Beta. In this study, electroencephalography (EEG) acquisition tool was utilized to collect brain signals from 40 subjects and objectively reflected stress features induced by virtual reality (VR) technology. The EEG signals were analyzed using Welch’s fast Fourier transform (FFT) to extract power spectral density (PSD) features which represented the power of a signal distributed over a range of frequencies. Slow wave versus fast wave (SW/FW) of EEG has been studied to discriminate stress from resting baseline. The results showed the Alpha/Beta ratio and Theta/Beta ratio are negatively correlated with stress and indicated that the power ratios can discriminate the data characteristics of brainwaves for stress assessment. Institute of Advanced Engineering and Science 2020-01 Article PeerReviewed Tee, Y. W. and Mohd. Aris, S. A. (2020) Electroencephalogram (eeg) stress analysis on alpha/beta ratio and theta/beta ratio. Indonesian Journal of Electrical Engineering and Computer Science, 17 (1). pp. 175-182. ISSN 2502-4752 http://www.dx.doi.org/10.11591/ijeecs.v17.i1.pp175-182 DOI: 10.11591/ijeecs.v17.i1.pp175-182
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology (General)
spellingShingle T Technology (General)
Tee, Y. W.
Mohd. Aris, S. A.
Electroencephalogram (eeg) stress analysis on alpha/beta ratio and theta/beta ratio
description This paper presents an analysis of stress feature using the power ratio of frequency bands including Alpha to Beta and Theta to Beta. In this study, electroencephalography (EEG) acquisition tool was utilized to collect brain signals from 40 subjects and objectively reflected stress features induced by virtual reality (VR) technology. The EEG signals were analyzed using Welch’s fast Fourier transform (FFT) to extract power spectral density (PSD) features which represented the power of a signal distributed over a range of frequencies. Slow wave versus fast wave (SW/FW) of EEG has been studied to discriminate stress from resting baseline. The results showed the Alpha/Beta ratio and Theta/Beta ratio are negatively correlated with stress and indicated that the power ratios can discriminate the data characteristics of brainwaves for stress assessment.
format Article
author Tee, Y. W.
Mohd. Aris, S. A.
author_facet Tee, Y. W.
Mohd. Aris, S. A.
author_sort Tee, Y. W.
title Electroencephalogram (eeg) stress analysis on alpha/beta ratio and theta/beta ratio
title_short Electroencephalogram (eeg) stress analysis on alpha/beta ratio and theta/beta ratio
title_full Electroencephalogram (eeg) stress analysis on alpha/beta ratio and theta/beta ratio
title_fullStr Electroencephalogram (eeg) stress analysis on alpha/beta ratio and theta/beta ratio
title_full_unstemmed Electroencephalogram (eeg) stress analysis on alpha/beta ratio and theta/beta ratio
title_sort electroencephalogram (eeg) stress analysis on alpha/beta ratio and theta/beta ratio
publisher Institute of Advanced Engineering and Science
publishDate 2020
url http://eprints.utm.my/id/eprint/87106/
http://www.dx.doi.org/10.11591/ijeecs.v17.i1.pp175-182
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