Development and Application of a Body Joint Angle Detection System for Free-Throw Shooting Prediction and Posture Correction - Cheng-Hsiu Li (International Journal of Engineering and Technology Innovation, 2025)
The success rate of free-throw shooting is often a critical factor in determining game outcomes. This study employs machine learning to develop a low-cost, hardware-free joint angle measurement system for free-throw shooting and applies it to the scientific training of free-throw shooting skills. With the system, the joint angle curves of players can be measured without the need for reflective markers, thereby reducing setup costs and facilitating the integration of scientific training. This study presents several innovative features. The experimental results indicate that the amount of training data required for modeling is 50% of that required by the J48 decision tree classifier, with an accuracy 1.2 times higher. Additionally, when a shot is missed, the system compares the disparity in joint angles and provides feedback for posture correction, allowing players to target specific problem areas for training, improve free-throw performance, and assist the team in winning games.