Alertness prediction system and method

A device for monitoring and predicting alertness of an individual, the device comprising:

• one or more sensors configured to obtain information signals about the individual, the sensors comprising at least one of:
• a motion sensor configured to produce movement data or body position data of the individual,
• a temperature sensor configured to produce distal skin temperature data of the individual, and
• a heart rate monitor configured to produce heart rate data of the individual;
• a memory configured to store:
• a default circadian rhythm configured to be refined with data derived from the information signals about the individual to generate an estimated circadian rhythm for the individual, and
• a bio-mathematical model configured to generate a fatigue score for the individual;
• a processor coupled to the one or more sensors and to the memory, configured to:
• receive the information signals about the individual,
• estimate a circadian rhythm of the individual by incorporating the information signals about the individual to refine the default circadian rhythm,
• extract features from the information signals about the individual and the estimated circadian rhythm,
• extract at least one coefficient from the extracted features using at least one pattern recognition algorithm or machine learning algorithm,
• apply the bio-mathematical model to the at least one extracted coefficient, and
• generate the fatigue score for the individual from the at least one extracted coefficient using the bio-mathematical model.