Recognition of Volleyball Player’s Arm Motion Trajectory and Muscle Injury Mechanism Analysis Based upon Neural Network Model

Abstract

At present, in sports training for volleyball, it still mainly depends on the personal experience of the coach. Training costs are high, and the quality is difficult to maintain stable. Even with the introduction of training assistance software, it is often necessary to manually enter complex data, and the research samples are mostly single individuals. Serving is one of the basic and important technical movements of volleyball, and its standardization is of great significance to the stable performance of the scene. This article proposes an analysis of the volleyball player’s arm trajectory based on the background of human posture recognition and analysis, based on the neural network model. The changes in the angles of the shoulders, elbows, and wrist when serving the ball reflect the different trajectories of the arm. Experiments show that the height of the throwing arm from the ground accounts for 98% of the height. The horizontal angle of the throwing arm at the moment the ball leaves the hand is positively correlated with the throwing time and height, and the reasonable trajectory has an impact on the stability of the throwing ball. The closer the trajectory of the tossing arm is to the vertical, the more stable the tossing is.