Sorry, you need to enable JavaScript to visit this website.

Estimating exercise-induced fatigue from thermal facial images

DOI:
10.60864/7k0w-yr70
Citation Author(s):
Submitted by:
Manuel Lage
Last updated:
6 June 2024 - 10:54am
Document Type:
Poster
Document Year:
2024
Event:
Presenters:
Manuel Lage Cañellas
Paper Code:
IVMSP-P16.7
 

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.

up
0 users have voted: