The rapid improvement of the economic level has led to the prosperity of sports, and the rehabilitation training of athletes has also developed rapidly and has attracted widespread attention from all over the world. How to make track and field athletes quickly relieve the negative impact of sports injuries on the body during rehabilitation training is the most concerned issue in the field of sports medicine today. The traditional rehabilitation training cycle is long, and the rehabilitation effect is very small, which cannot fundamentally eliminate the injury and restore the athletes’ various physical functions and sports qualities to the original level. This article combines the latest artificial intelligence and virtual reality technology to analyze the causes and control strategies of athletes’ injuries and to understand the reasons for the injuries of track and field athletes in daily training and the various factors that affect their rehabilitation. And it was used in rehabilitation training practice and analyzed from four aspects: body shape, physical function, sports quality, and rehabilitation effect. The experimental results show that the rehabilitation training using artificial intelligence and virtual reality technology can make the athletes’ physical function recover more than 96%, and the overall average rehabilitation effect can reach 93.79 points, which is feasible to a certain extent. The application of artificial intelligence and virtual reality technology to the current stage of rehabilitation training can effectively improve the rehabilitation effect of track and field athletes.
As a popular competitive sport, basketball has attracted the attention of many people due to its warm and sunny characteristics. Athletics means results, but not everyone gets the results they want. With the continuous development of technology, people have gradually discovered that the physical function of athletes is one of the important factors affecting the performance of sports. The long-standing principle of “three big and one small” ignores the overall physical fitness of athletes, resulting in insufficient physical coordination and slow performance improvement. Competitive sports have always followed the principle of “three big and one small,” which means emphasizing high-strength and high-intensity training, and fundamentally ignoring the impact of small muscle groups and overall physical fitness on athletes. To overcome this disadvantage, this paper aims to study the physical condition monitoring of basketball players based on the Internet of Things and blockchain. It is expected to use the Internet of Things and blockchain technology to monitor the physical function of athletes in real time, formulate scientific training plans, and improve athletes’ competition. The essence of blockchain is a decentralized database, which is used to verify the validity of messages. With the promotion of Internet technology, it is essential to store and extract information from large network information. This paper compared the results of experimental methods to show the impact of the connection between physical function training and high-level basketball traditional training, proposed a new scalable storage and privacy protection scheme to solve the problem that a large amount of data cannot be stored on the blockchain. The experimental results in this paper showed that the lowest hemoglobin content of athletes before training was 131 g/L, and the highest was 157 g/L, indicating that the athletes were generally in good physical condition at this moment. After training, the lowest hemoglobin content of athletes was 117 g/L and the highest was 131 g/L, indicating that the athlete’s physical function state declined and the training intensity was too high.
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