Stress Monitoring Using GSR in People with Anxiety Disorder and Analysis Using Optimization Algorithms

This is the authors' abstract. We don't add key points for this paper.

Purpose: Anxiety disorder is a serious issue that leads to depression, which in turn causes various physical and mental health problems. Monitoring the level of stress in people with anxiety disorder is very important, considering they often fall into panic attack episodes when anxiety levels increase. Methods: In this work, a study is conducted among eleven people by assigning a critical task and monitoring the level of stress using a GSR V 2.0 sensor and an Arduino microcontroller. The obtained EDA signals are processed and analyzed using a convex optimization-based algorithm (cvxEDA) for decomposing the GSR signal and a Trough-to-Peak algorithm for measuring the number of peaks in the SCR. Results: The findings indicate an increase in stress reactivity when subjected to critical tasks. Stress levels are categorized based on the number of peaks in the SCR. Conclusion: The proposed work can aid clinical psychologists in assessing human stress levels non-invasively and is also very costeffective.