IEICE TRANSACTIONS on Information
Quantification of Human Stress Using Commercially Available Single Channel EEG Headset
Summary :
A study on quantification of human stress using low beta waves of electroencephalography (EEG) is presented. For the very first time the importance of low beta waves as a feature for quantification of human stress is highlighted. In this study, there were twenty-eight participants who filled the Perceived Stress Scale (PSS) questionnaire and recorded their EEG in closed eye condition by using a commercially available single channel EEG headset placed at frontal site. On the regression analysis of beta waves extracted from recorded EEG, it has been observed that low beta waves can predict PSS scores with a confidence level of 94%. Consequently, when low beta wave is used as a feature with the Naive Bayes algorithm for classification of stress level, it not only reduces the computational cost by 7 folds but also improves the accuracy to 71.4%.
- Publication
- IEICE TRANSACTIONS on Information Vol.E100-D No.9 pp.2241-2244
- Publication Date
- 2017/09/01
- Publicized
- 2017/06/02
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2016EDL8248
- Type of Manuscript
- LETTER
- Category
- Human-computer Interaction
Authors
Sanay MUHAMMAD UMAR SAEED
University of Engineering and Technology
Syed MUHAMMAD ANWAR
University of Engineering and Technology
Muhammad MAJID
University of Engineering and Technology
Keyword
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Sanay MUHAMMAD UMAR SAEED, Syed MUHAMMAD ANWAR, Muhammad MAJID, "Quantification of Human Stress Using Commercially Available Single Channel EEG Headset" in IEICE TRANSACTIONS on Information,
vol. E100-D, no. 9, pp. 2241-2244, September 2017, doi: 10.1587/transinf.2016EDL8248.
Abstract: A study on quantification of human stress using low beta waves of electroencephalography (EEG) is presented. For the very first time the importance of low beta waves as a feature for quantification of human stress is highlighted. In this study, there were twenty-eight participants who filled the Perceived Stress Scale (PSS) questionnaire and recorded their EEG in closed eye condition by using a commercially available single channel EEG headset placed at frontal site. On the regression analysis of beta waves extracted from recorded EEG, it has been observed that low beta waves can predict PSS scores with a confidence level of 94%. Consequently, when low beta wave is used as a feature with the Naive Bayes algorithm for classification of stress level, it not only reduces the computational cost by 7 folds but also improves the accuracy to 71.4%.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2016EDL8248/_p
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@ARTICLE{e100-d_9_2241,
author={Sanay MUHAMMAD UMAR SAEED, Syed MUHAMMAD ANWAR, Muhammad MAJID, },
journal={IEICE TRANSACTIONS on Information},
title={Quantification of Human Stress Using Commercially Available Single Channel EEG Headset},
year={2017},
volume={E100-D},
number={9},
pages={2241-2244},
abstract={A study on quantification of human stress using low beta waves of electroencephalography (EEG) is presented. For the very first time the importance of low beta waves as a feature for quantification of human stress is highlighted. In this study, there were twenty-eight participants who filled the Perceived Stress Scale (PSS) questionnaire and recorded their EEG in closed eye condition by using a commercially available single channel EEG headset placed at frontal site. On the regression analysis of beta waves extracted from recorded EEG, it has been observed that low beta waves can predict PSS scores with a confidence level of 94%. Consequently, when low beta wave is used as a feature with the Naive Bayes algorithm for classification of stress level, it not only reduces the computational cost by 7 folds but also improves the accuracy to 71.4%.},
keywords={},
doi={10.1587/transinf.2016EDL8248},
ISSN={1745-1361},
month={September},}
Copy
TY - JOUR
TI - Quantification of Human Stress Using Commercially Available Single Channel EEG Headset
T2 - IEICE TRANSACTIONS on Information
SP - 2241
EP - 2244
AU - Sanay MUHAMMAD UMAR SAEED
AU - Syed MUHAMMAD ANWAR
AU - Muhammad MAJID
PY - 2017
DO - 10.1587/transinf.2016EDL8248
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E100-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2017
AB - A study on quantification of human stress using low beta waves of electroencephalography (EEG) is presented. For the very first time the importance of low beta waves as a feature for quantification of human stress is highlighted. In this study, there were twenty-eight participants who filled the Perceived Stress Scale (PSS) questionnaire and recorded their EEG in closed eye condition by using a commercially available single channel EEG headset placed at frontal site. On the regression analysis of beta waves extracted from recorded EEG, it has been observed that low beta waves can predict PSS scores with a confidence level of 94%. Consequently, when low beta wave is used as a feature with the Naive Bayes algorithm for classification of stress level, it not only reduces the computational cost by 7 folds but also improves the accuracy to 71.4%.
ER -
English
