Unordinary situation assessment of human fatigue and drowsiness in expert decision-making systems

The current research aims to augment a platform with complex passive multi-level fatigue and workability evaluation and the monitoring system for integration into professional safety and telehealth domains. The monitoring and decision-making system offers a comprehensive evaluation of human fatigue based on estimating mental and physical types of human fatigue. The aggregated component values express the fuzzy logicbased decision about the overall fatigue level in the system output. The current paper offers a decision-making approach for a rule-based expert system in unordinary situations of fatigue and drowsiness as an additional decision block. Evaluating unordinary situations uses electroencephalography parameters of a wearable device in combination with information from pre-work questionnaires. The unordinary situation model evaluates the presence of 5 additional conditions: insomnia, last sleep, microsleep, daytime sleepiness, and boredom sleepiness. The system performs additional control tasks to trigger alerts based on the new decisions during the monitoring session. The feedback, such as decisions, alerts, and recommendations, is received through a smartphone or wearable equipment. The system addition described in this work uses recommendations for the system user to express the level of fatigue and the proposed alerting expert decision model outputs immediate alerts, thus preventing drivers or operators from falling asleep. The proposed system aims to benefit in areas of work schedule planning and dangerous, responsible work.