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DIGITAL MENTAL HEALTH MONITORING AND STRESS DETECTION SYSTEM

R.Kanishka Raj, N. Gayathri, N. Mahmuthal

Abstract


This project focuses on detecting and analyzing stress levels among students using multiple parameters such as academic pressure, emotional state, lifestyle habits, and social interaction. The system calculates a stress score and categorizes it into different levels such as low, medium, and high stress. Based on the results, personalized suggestions are provided to help users improve their mental well-being. Additionally, a chatbot is integrated to offer real-time guidance and support. The system also includes trend visualization to track stress levels over time.


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References


Smith, J., & Brown, A., “Student Stress and Mental Health Analysis in Academic Environments,” Journal of Educational Research, 2020.

Kumar, R., & Sharma, P., “Web-Based Stress Detection Systems Using Questionnaire Models,” International Journal of Computer Applications, 2019.

Lee, H., et al., “Machine Learning Approaches for Stress Prediction Using Behavioral Data,” IEEE Transactions on Affective Computing, 2021.

Patel, S., & Verma, D., “Mobile Applications for Mental Health Monitoring and Support,” International Journal of Advanced Technology, 2020.

Ahmed, K., et al., “Rule-Based Chatbot for Mental Health Assistance,” Procedia Computer Science, 2022.

Johnson, M., “Visualization Techniques for Health Data Analysis,” IEEE Access, 2019.


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