Enhancing urban wellness: real-time workout posture monitoring with human pose estimation and joint angle analysis using MediaPipe and OpenCV

This paper presents an innovative Real-time Monitoring System for precise workout posture correction, leveraging MediaPipe and OpenCV technologies. Designed to enhance urban wellness, the system accurately tracks joint angles through sophisticated algorithms, making it ideal for applications ranging from general fitness to rehabilitation. Accurate joint angle calculations facilitate the evaluation of users' range of motion, muscle strength, and balance, significantly contributing to injury prevention and improved exercise techniques. The objectives encompass system construction, analysis of effectiveness, and validation in accordance with Disease Control and Prevention (CDC) guidelines. By employing BlazePose Model for instantaneous pose estimation, the system precisely computes the angles of the joints, guaranteeing accurate workout posture during dynamic actions such as squats and push-ups. The results indicate that the system is highly successful in promptly and accurately evaluating angles, hence fulfilling the requirement for monitoring workout posture in real-time.