Estimating exercise-induced fatigue from thermal facial images

• URL: http://arxiv.org/abs/2309.06095v1
• Date: Tue, 12 Sep 2023 10:00:23 GMT
• Title: Estimating exercise-induced fatigue from thermal facial images
• Authors: Manuel Lage Ca\~nellas, Constantino \'Alvarez Casado, Le Nguyen, Miguel Bordallo L\'opez
• Abstract summary: We present an automated method for estimating exercise-induced fatigue levels using thermal imaging and facial analysis techniques. Our results suggest that exercise-induced fatigue levels could be predicted with only one static thermal frame with an average error smaller than 15%.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Exercise-induced fatigue resulting from physical activity can be an early indicator of overtraining, illness, or other health issues. In this article, 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.

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