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.

本文综述了心理疲劳的理论模型、关键的技术手段和最新的人类疲劳生物传感技术，发现 EEG 传感器能够提供对疲劳检测的中等到良好的灵敏度，并讨论了可穿戴 EEG 以及环境传感器相互融合在实时监测方面的关键性作用和未来的发展方向。