Application of Biomechanics Based on Intelligent Technology and Big Data in Physical Fitness Training of Athletes

Abstract

Physical training has a high degree of participation all over the world. With the opening of the era of national fitness, physical training has become more popular from the original specialization, and the complex training methods and contents have gradually become simplified. The development and change of physical training has also brought many problems to the professional training of athletes, such as high training intensity but poor effect, insufficient training posture, and long-term physical injury. In order to help athletes achieve better results in physical training and reduce the probability of injury, taking sprint training as an example, this article adopted the sports and body data of elite athletes through intelligent technology and big data analysis, established a human motion model from the perspective of biomechanics, and then conducted a corresponding test run experiment for athletes. The experimental results suggested that drag resistance running could improve the specific strength quality of sprinting. At the same time, when using resistance load for training, the maximum speed should not exceed 90% of the maximum speed without resistance. The average horizontal maximum velocity decreased by approximately 9% when training under a resistance load, and the best training results were obtained by training athletes within this range.