Stress Monitoring and Management System
B Reshma, J Adithya, M Bhoomika, Naveen S R, N. K. Jisy, R Vinu · 2024
Stress is a pervasive and debilitating condition that affects individuals across various aspects of work in day-to-day life. The first aspect involves vigilant observation of physical, emotional, and behavioral symptoms to identify stressors. Physical signs, such as headaches and changes in appetite, emotional indicators like anxiety and irritability, and behavioral changes, such as social withdrawal, serve as key markers for stress assessment. Stress management is a proactive approach to mitigate the impact of stress on overall well-being. However, with the advent of technology, various tools and applications have emerged to assist in stress monitoring and management. Our approach involves the use of a machine learning (ML) algorithm to analyze the data that is collected by the sensors and communicated with the help of Raspberry Pi. The results indicate that the Decision Tree algorithm provides significant accuracy of 98.4 % with an F1 score of 0.98. This data is then used to analyze the current state of the user and provide haptic feedback if necessary.