Sleep debt and the disruption to daily biological rhythms caused by various factors (long duty periods, irregular working hours, night flights, etc.) mean that pilots have to constantly push back their biological limits. Pilots' mental workload also varies considerably during a flight. High during the critical phases (take-off and landing), it becomes very low during the cruising phases. When the mental load becomes too high or, conversely, too low, performance deteriorates and piloting errors can occur. In this context, the implementation of methods for detecting the state of drowsiness and the level of mental load, in near-real time, represents a major challenge for the monitoring and control of piloting activity.
