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@article{174954,
        author = {Goutham Regi and Divya Sunny},
        title = {MindTrack AI-Based Mental Health Monitoring System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {979-984},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174954},
        abstract = {Mental health is one of the most neglected areas of health, and it is a growing concern today.This paper presents MindTrack,an AI-powered system that continuously monitors mental health using facial emotion recognition. By using pre- trained deep learning models from Hugging Face, the system captures facial expressions and analyzes them in real time,then generates some mental health exercises if the user is in a negative space of mind. The framework integrates Streamlit for UI, OpenCV for image processing, and Ultralytics YOLO for face detection. Users receive instant insights via a pop- up in the web interface, and historical emotion trends are visualized for further analysis. The proposed system improves accessibility and efficiency in mental health assessment, reducing the need for manual intervention. This paper details the technical architecture, implementation, and future enhancements of the MindTrack system.},
        keywords = {Facial emotion recognition, AI-powered mental health monitoring, Deep learning, Mental Health Exercise rec- ommendations,},
        month = {April},
        }