Mental fatigue is a leading cause of motor vehicle accidents, medical errors,
loss of workplace productivity, and student disengagements in e-learning
environment. Development of sensors and systems that can reliably track mental
fatigue can prevent accidents, reduce errors, and help increase workplace
productivity. This review provides a critical summary of theoretical models of
mental fatigue, a description of key enabling sensor technologies, and a
systematic review of recent studies using biosensor-based systems for tracking
mental fatigue in humans. We conducted a systematic search and review of recent
literature which focused on detection and tracking of mental fatigue in humans.
The search yielded 57 studies (N=1082), majority of which used
electroencephalography (EEG) based sensors for tracking mental fatigue. We
found that EEG-based sensors can provide a moderate to good sensitivity for
fatigue detection. Notably, we found no incremental benefit of using
high-density EEG sensors for application in mental fatigue detection. Given the
findings, we provide a critical discussion on the integration of wearable EEG
and ambient sensors in the context of achieving real-world monitoring. Future
work required to advance and adapt the technologies toward widespread
deployment of wearable sensors and systems for fatigue monitoring in
semi-autonomous and autonomous industries is examined.Comment: 19 Pages, 3 Figure