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@article{192360,
        author = {Sumedh Sonawane and Sakshi Mohite and Dnyaneshwari Shendkar and Soham Wanzare},
        title = {Relaxify: AI-Based Real-Time Employee Health Monitoring and Exercise Guidance System Using Computer Vision},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {1524-1527},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192360},
        abstract = {Modern workplace environments demand employees to work for prolonged hours in front of computers, often resulting in sedentary lifestyles and physical health problems such as neck stiffness, shoulder pain, fatigue, and posture-related disorders. These health concerns not only reduce employee productivity but also increase long-term medical risks and absenteeism in organizations. Traditional health monitoring solutions rely heavily on wearable devices or manual exercise reminders, which may not always be convenient or consistently followed by employees. This paper presents Relaxify, an AI-based real-time employee health monitoring and exercise guidance system designed specifically for workplace environments. The proposed system utilizes computer vision techniques through a webcam to automatically detect employee presence and guide them to perform office-friendly stretching exercises. The system focuses primarily on neck and shoulder exercises to reduce muscle strain caused by prolonged sitting. Using pose estimation and movement detection algorithms, the system monitors exercise performance, accurately counts repetitions, and stores participation data for tracking employee wellness progress over time. The system operates as desktop software, enabling easy deployment without additional hardware or wearable sensors. Automated reminders and exercise monitoring encourage employees to maintain healthy work habits. Experimental implementation demonstrates reliable real-time exercise detection and counting performance under normal office conditions. The system contributes toward smart workplace wellness solutions by providing a non- intrusive and cost-effective monitoring approach. Future improvements may include posture correction mechanisms, additional exercise modules, and integration with organizational health dashboards for large-scale monitoring.},
        keywords = {},
        month = {February},
        }