Simple jQuery Dropdowns
Please use this identifier to cite or link to this item:
Title: EEG-based mental fatigue alarm system using weighted-frequency index
Authors: Yunyong Punsawad
Sittichai Aempedchr
Yodchanan Wongsawat
Manukid Parnichkun
Mahidol University
Asian Institute of Technology Thailand
Keywords: Computer Science
Issue Date: 1-Dec-2010
Citation: APSIPA ASC 2010 - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. (2010), 193-196
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.
Appears in Collections:Scopus 2006-2010

Files in This Item:
There are no files associated with this item.

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