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@article{171529,
        author = {Vadlamuru Dhana Sri Hima and Dasari Vyshnavi Krishna and G.Raju and B. Marcus sashank},
        title = {Posture Detection Using MoveNet},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {8},
        pages = {382-387},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=171529},
        abstract = {Posture detection plays a critical role in applications such as fitness tracking, ergonomic assessment, and rehabilitation. Traditional methods for posture evaluation often demand intricate hardware setups and specialized software, posing challenges for broad adoption. This project introduces MoveNet, a cutting-edge machine learning model designed to serve as the core of a real-time posture detection system. MoveNet efficiently estimates human poses using a single camera, identifying key body landmarks with high precision. Tensor Flow Lite powers the system and leverages Python for real-time processing in machine learning applications, ensuring cross-platform compatibility without the need for specialized hardware. By providing accurate posture detection and feedback on body alignment, MoveNet demonstrates adaptability to a wide array of use cases, including fitness coaching, rehabilitation exercises, and ergonomic monitoring.},
        keywords = {},
        month = {December},
        }