Publication: EEG-based mental fatigue alarm system using weighted-frequency index
10
Issued Date
2010-12-01
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2-s2.0-79958169810
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Mahidol University
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SCOPUS
Bibliographic Citation
APSIPA ASC 2010 - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. (2010), 193-196
Suggested Citation
Yunyong Punsawad, Sittichai Aempedchr, Yodchanan Wongsawat, Manukid Parnichkun EEG-based mental fatigue alarm system using weighted-frequency index. APSIPA ASC 2010 - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. (2010), 193-196. Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/28977
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Title
EEG-based mental fatigue alarm system using weighted-frequency index
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Abstract
Mental fatigue is another major cause of the serious car accidents. Ability to early predict the mental fatigue phenomenon is hence one of the challenging problems in brain-computer interface (BCI). In this paper, we propose the practical EEG-based mental fatigue alarm system including the weighted-frequency index of the linear combination among EEG theta, alpha and beta rhythms. The proposed system is tested with the simulated driving situations. By using only 1-channel EEG at the temporal area of the brain, more than 90% of prediction accuracies are reported compared to the opinion scores of the users.