Citation

Eoh HJ, Chung MK, Kim SH. Int. J. Ind. Ergonomics 2005; 35(4): 307-320.

Copyright

(Copyright © 2005, Elsevier Publishing)

DOI

unavailable

PMID

unavailable

Abstract

Drivers' drowsiness is one of the main causes of car accidents or near-missed accidents. This has been proven by many studies that established links between driver's drowsiness and road accidents. The objective of this study was to analyze the EEG changes in fatigued subjects while performing a simulated driving task. After a night of sleep deprivation, eight subjects were given a dose of caffeine to reduce drowsiness. During about 50 min of continuous driving, car movements and subject behaviors were recorded on video cameras, and 8 channels of EEG were also recorded. Three basic indices, three ratio indices, and two burst indices were calculated from preprocessed EEG signals. EEG [alpha],[beta], [beta]/[alpha] and ([alpha]+[theta])/[beta] indices showed significant differences between driving periods. In the comparison of road type, EEG [alpha],[beta], [beta]/[alpha] and ([alpha]+[theta])/[beta] indices of the straight section of the driving task were significantly different from those of the curved section. This study also analyzed EEG changes before and after car accidents, showing that [beta] and ([alpha]+[theta])/[beta] were related to the mental alertness level. In the analysis of burst activity, [theta] burst activity, which was not significant in the mean power analysis, was significantly different between driving sessions.Relevance to IndustryDriver's drowsiness is a major cause of serious traffic accidents. This study deals with time variant EEG change of sleep-deprived drivers--an important aspect of driver drowsiness analysis.The result of this study can be used to estimate overall alertness level of drivers.