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Assistant Training System of Teenagers’ Physical Ability Based on Artificial Intelligence

机译:基于人工智能的青少年物理能力助理培训体系

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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.
机译:人工智能技术的快速发展使其广泛应用于各种领域。为了更科学地协助青少年体育培训,本文开发了一套基于人工智能技术的青少年体育训练系统。首先,建立了实验平台,并且传感器节点通过串行端口与测试主机连接,以将数据收集到实验平台。该系统由目标检测模块,数据分析模块和人体姿势估计模块组成。基于Vibe模型的背景建模方法用于形成目标检测模块,并且使用Canny Edge检测算法来形成数据分析模块。最后,建立了姿势辅助指数以估计人类姿势。本文对青年运动队进行了系统的应用测试。实验组接受了基于人工智能的物理训练系统的培训,而对照组培训具有传统培训方法。在实验之前,评估了两组受试者的身体健康,包括延长跳跃,50米Sprint,30?S单挥杆绳索跳过,上拉和蹲下1RM。在训练3和6周后,再次评估物理健身。实验结果表明,本文建立的智能助理系统可以准确地表明运动员的生理负荷符合生理功能变化的规律。经过六周的训练后,实验组的延长跳跃已经提高了20.97厘米,50米的仪表时加速了1.21?S,30秒的单个挥杆绳已经增加13.76,上拉已增加1.41,下蹲1RM已增加15.16。这表明基于人工智能的辅助训练系统可以帮助年轻运动员提高身体素质,提高他们的体育技能。

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