Novel Approach for Real-Time Exercise Posture Correction Using Computer Vision and Cnn

In recent years, there has been an increased focus on physical fitness, this underscores the need for proper exercise form to prevent injuries and maximize benefits. This paper presents a system that employs Computer Vision and Machine Learning for Real-Time Exercise correction. By analyzing exercise videos and utilizing pose estimation algorithms, the system identifies incorrect postures and provides immediate Feedback to users, ensuring correct exercise execution. The study's findings demonstrate that the proposed system achieves a high level of accuracy in detecting incorrect postures, thereby enhancing exercise safety and efficacy. By ensuring proper form, our system has the potential to be an effective tool for individuals looking to optimize their workout routines for a healthier lifestyle.