Anxolotl, an Anxiety Companion App -- Stress Detection

Autor:	Gomes, Nuno, Pato, Matilde, Santos, Pedro, Lourenço, André, Rodrigues, Lourenço
Rok vydání:	2022
Předmět:	Electrical Engineering and Systems Science - Signal Processing Computer Science - Human-Computer Interaction Computer Science - Machine Learning J.3 I.5.5 I.5.4
Druh dokumentu:	Working Paper
Popis:	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. Comment: 7 pages, 3 figures, 2 tables IEEE 44th International Engineering in Medicine and Biology Conference
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2212.14006 Zobrazit plný text záznamu View this record from Arxiv