Virtual Booth

This project develops an integrated system for enhanced running performance analysis and injury prediction through motion capture technology. The system combines OpenPose-based markerless motion tracking with CNN gait analysis, XGBoost machine learning for training data-based injury prediction, and wearable LSM6DS3 sensors for stride and speed measurement. A unified GUI integrates all components, enabling real-time biomechanical assessment and proactive injury intervention. The system addresses limitations of traditional coaching methods by providing data-driven insights into movement patterns, training loads, and injury risks. Testing demonstrates high accuracy in keypoint detection and gait metric prediction, offering coaches and athletes comprehensive tools for performance optimization while supporting sustainable sports science practices and contributing to SDG 3 (Good Health and Well-Being) and SDG 9 (Industry, Innovation and Infrastructure).