ArXiv Preprint
Stress has a great effect on people's lives that can not be understated.
While it can be good, since it helps humans to adapt to new and different
situations, it can also be harmful when not dealt with properly, leading to
chronic stress. The objective of this paper is developing a stress monitoring
solution, that can be used in real life, while being able to tackle this
challenge in a positive way. The SMILE data set was provided to team Anxolotl,
and all it was needed was to develop a robust model. We developed a supervised
learning model for classification in Python, presenting the final result of
64.1% in accuracy and a f1-score of 54.96%. The resulting solution stood the
robustness test, presenting low variation between runs, which was a major point
for it's possible integration in the Anxolotl app in the future.
Nuno Gomes, Matilde Pato, Pedro Santos, André Lourenço, Lourenço Rodrigues
2022-12-28
