Detecting Driver Mental Fatigue Based on Eeg Alpha Power Changes During Simulated Driving



Gharagozlou F¹ ; Saraji GN¹ ; Mazloumi A¹ ; Nahvi A² ; Nasrabadi AM³ ; Foroushani AR⁴ ; Kheradmand AA⁵ ; Ashouri M² ; Samavati M⁶
Source: Iranian Journal of Public Health Published:2015

Abstract

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. © 2015, Iranian Journal of Public Health. All rights reserved.