Fatigue is a significant risk factor contributing to accidents in the transportation sector, particularly in bus operations. Signs of fatigue can be identified using fatigue detection technologies. However, there is still ongoing debate regarding which parameter is most effective for detecting fatigue. This study aimed to identify the most sensitive parameters for fatigue detection. A total of 15 participants were included in this within-subject study, in which each participant completed both a baseline condition and a fatigue condition involving 24 h of wakefulness. The results of the study revealed that the percent miss of the Sustained Attention Test (SAT) is a parameter that effectively predicts fatigue. Additionally, the mean Psychomotor Vigilance Test (PVT) and minor lapses PVT demonstrated excellent accuracy in detecting fatigue. Twenty-four-hour sleep deprivation was associated with significantly increased levels of fatigue.
Didin et al. (Sat,) studied this question.