Estimating Exercise-Induced Fatigue from Thermal Facial Images

Exercise-induced fatigue resulting from physical activity can be an early indicator of overtraining, illness, or other health issues. In this paper, we present an automated method for estimating exercise-induced fatigue levels through the use of thermal imaging and facial analysis techniques utilizing deep learning models. Leveraging a novel dataset comprising over 400,000 thermal facial images of rested and fatigued users, our results suggest that exercise-induced fatigue levels could be predicted with only one static thermal frame with an average error smaller than 15%. The results emphasize the viability of using thermal imaging in conjunction with deep learning for reliable exercise-induced fatigue estimation.