Detecting Driver Mental Fatigue Based on EEG Alpha Power Changes during Simulated Driving

Background: driver fatigue is one of the major implications in transportation safety and accounted for up to 40% of road accidents. this study aimed to analyze the eeg alpha power changes in partially sleep-deprived drivers while performing a simulated driving task. methods: twelve healthy male car drivers participated in an overnight study. continuous eeg and eog records were taken during driving on a virtual reality simulator on a monotonous road. simultaneously, video recordings from the driver face and behavior were performed in lateral and front views and rated by two trained observers. moreover, the subjective self-assessment of fatigue was implemented in every 10-min interval during the driving using fatigue visual analog scale (f-vas). power spectrum density and fast fourier transform (fft) were used to determine the absolute and relative alpha powers in the initial and final 10 minutes of driving. results: the findings showed a significant increase in the absolute alpha power (p = 0.006) as well as f-vas scores during the final section of driving (p = 0.001). meanwhile, video ratings were consistent with subjective self-assessment of fatigue. conclusion: the increase in alpha power in the final section of driving indicates the decrease in the level of alertness and attention and the onset of fatigue, which was consistent with f-vas and video ratings. the study suggested that variations in alpha power could be a good indicator for driver mental fatigue, but for using as a countermeasure device needed further investigations.