Description:
<jats:p>The rapid development of artificial intelligence technology makes it widely used in various fields. In order to more scientifically assist teenagers in physical training, this paper develops a set of teenagers’ physical training system based on artificial intelligence technology. Firstly, the experimental platform is built, and the sensor nodes are connected with the test host through the serial port to collect data to the experimental platform. The system consists of target detection module, data analysis module, and human posture estimation module. The background modeling method based on vibe model is used to form the target detection module, and the canny edge detection algorithm is used to form the data analysis module. Finally, the posture auxiliary index is established to estimate the human posture. This paper makes a systematic application test on a youth sports team. The experimental group was trained with artificial intelligence-based physical training system, while the control group was trained with traditional training methods. Before the experiment, the physical fitness of the two groups of subjects were evaluated, including standing long jump, 50 meters sprint, 30 s single swing rope skipping, pull-up, and squat 1RM. After 3 and 6 weeks of training, the physical fitness was evaluated again. The experimental results show that the intelligent assistant system established in this paper can accurately show that the physiological load of the athlete is in line with the law of physiological function change. After six weeks of training, the standing long jump of the experimental group has been improved by 20.97 cm, the 50 meters dash has been accelerated by 1.21 s, the 30 second single swing rope has been increased by 13.76, the pull-up has been increased by 1.41, and the squat 1RM has been increased by 15.16. This shows that the auxiliary training system based on artificial intelligence can help young athletes improve their physical quality and enhance their sports skills.</jats:p>