Abstract
Tennis requires a high level of physical fitness, which requires the coordination and cooperation of all parts of the body. Sports injury is inevitable even for advanced professional students and athletes. Sports injury prevention has become an important task of tennis players' training and management. The aim of this paper is to explore a new method to prevent sports injury of tennis players based on optical imaging detection of cluster analysis. The optical imaging data of athletes are collected and processed by cluster analysis method. Firstly, image processing algorithm is used to extract feature points. Then cluster analysis method is used to cluster the feature points to obtain the movement characteristics of different parts of athletes. Finally, according to the obtained sports characteristics, a set of sports injury prevention strategy is designed. By training the sports data of different groups, the risk of Sports injury that athletes may face is predicted. The results show that the computer method of cluster analysis and Gaussian process regression can effectively predict the risk of Sports injury of tennis players, and provide corresponding prevention suggestions. This is of great significance to the management and training of tennis players, which helps to reduce the occurrence of Sports injury and improve the performance level and career durability of athletes.
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QW has done the first version, NY has done the simulations. All authors have contributed to the paper’s analysis, discussion, writing, and revision.
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Wang, Q., Yao, N. Light imaging detection based on cluster analysis for the prevention of sports injury in tennis players. Opt Quant Electron 56, 191 (2024). https://doi.org/10.1007/s11082-023-05803-8
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DOI: https://doi.org/10.1007/s11082-023-05803-8