Drowsiness assessment using electroencephalogram in driving simulator environment

Abstract

Traffic accident is one of the most important problems in many countries. One of traffic accident causes is drowsiness. Many studies have been done to solve this problem. One of them is to capture the driver's face expression and estimate the driver's drowsiness. Besides measuring the driver's physiological condition and use it to predict one's drowsiness is also considered. Since drowsiness is strongly related to human brain, by assessing drowsiness using biological signal especially brain signal become the most promising approach to evaluate drowsiness. We proposed a study to investigate the relationship between drowsiness and physiological condition by employing electroencephalogram (EEG) signal and Japanese version of Karolinska sleepiness scale (KSS-J) in driving simulator environment. The result showed alpha band power of EEG signal from occipital lobe in drowsy condition (KSS-J ≥ 7) increased significantly compared with that in alert condition (KSS-J <; 7) with P <; 0.001. Therefore, it is suggested that EEG is effective to find the drowsiness in driving simulator environment.