Predicting Fatigue Impairment for Industry
Abstract
Human performance can be critically impacted by fatigue resulting from inadequate sleep. In a technological society, the consequences of fatigue related inattention or impaired response time are greater than ever. Industries such as aviation, rail, trucking, and medicine are mandated to have a Fatigue Management System (FMS) in place to ensure their personnel are ready for duty. We are testing the idea that a commercial, off the shelf (COTS) smart watch application using a new biomathematical model can provide continuous, obvious, real-time predictions about the wearer’s level of fatigue impairment. Our evidence shows that the correlation between a clinically approved measure with that of our smart watch application is strong enough to warrant applied trials with industry. We will also report on the correlation between subjective fatigue measures and the model’s fatigue predictions of subjective fatigue score throughout the waking hours. The conclusion of this study may show that continuous prediction of fatigue is possible hours before the point of endangerment, particularly for those industries requiring FMS to ensure public safety.
Predicting Fatigue Impairment for Industry
Human performance can be critically impacted by fatigue resulting from inadequate sleep. In a technological society, the consequences of fatigue related inattention or impaired response time are greater than ever. Industries such as aviation, rail, trucking, and medicine are mandated to have a Fatigue Management System (FMS) in place to ensure their personnel are ready for duty. We are testing the idea that a commercial, off the shelf (COTS) smart watch application using a new biomathematical model can provide continuous, obvious, real-time predictions about the wearer’s level of fatigue impairment. Our evidence shows that the correlation between a clinically approved measure with that of our smart watch application is strong enough to warrant applied trials with industry. We will also report on the correlation between subjective fatigue measures and the model’s fatigue predictions of subjective fatigue score throughout the waking hours. The conclusion of this study may show that continuous prediction of fatigue is possible hours before the point of endangerment, particularly for those industries requiring FMS to ensure public safety.