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Anxolotl, an Anxiety Companion App -- Stress Detection

arXiv 2212.14006 ↗First posted 28 Dec 2022eess.SP cs.HC cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 1 of its 16 references that are in the map. First posted on arXiv 28 Dec 2022.

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References · 1

  1. 2021ReLearn: A Robust Machine Learning Framework in Presence of Missing Data for Multimodal Stress Detection from Physiological Signalscited by 3

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