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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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 |
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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. |
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Article |
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Tee, Y. W. Mohd. Aris, S. A. |
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Tee, Y. W. Mohd. Aris, S. A. |
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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 |
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Electroencephalogram (eeg) stress analysis on alpha/beta ratio and theta/beta ratio |
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electroencephalogram (eeg) stress analysis on alpha/beta ratio and theta/beta ratio |
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Institute of Advanced Engineering and Science |
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2020 |
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http://eprints.utm.my/id/eprint/87106/ http://www.dx.doi.org/10.11591/ijeecs.v17.i1.pp175-182 |
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