Physical fitness refers to the general term for the physical fitness level of athletes, which is the ability to train in daily life. Over the years, with the continuous development of various training technology products, many new big data and other technologies have played an important role and function in improving the technical level of athletes' physical fitness. The body has the ability to hide in the body in terms of body structure, function and regulation, material energy conversion and storage, etc., as well as the comprehensive exercise ability displayed through the external environment. Therefore, sports training are the main means of development and improvement. Physical fitness is one whose magnitude cannot be measured with complete clarity. For a long time, the enhancement of physical fitness and the consumption of physical energy during the scientific and rational arrangement of the game have relied on the experience and experience of the coach. However, many times it is not very scientific and accurate, especially at the basic level of training. There is a lack of efficient physical fitness monitoring and analysis systems to provide coaches and athletes with scientific support for physical fitness training. The method of physical training also stays at the level of experience, and it is impossible to better combine traditional theory and practical data, resulting in more professional and accurate training methods and methods. Therefore, this paper designs a set of athlete physical training assistant system based on the decision support layer of the comprehensive health management system. It could provide strong technical support for athletes to scientifically and rationally use physical fitness, master their own physical fitness characteristics, and better play their competitive level. According to the above test results, this paper concluded that the system could support 25 DAT terminals under the pressure environment generated by the input data of the stress test, and the pressure requests 10 packets per second. The fault-tolerant transmission distance was 220M, and the fault-tolerant transmission distance was 60M, with strong fault tolerance. Test results demonstrated that the system was qualified and met the established requirements.

Zhou Zhou, Jian Li. Design of Physical Training Assistant System Based on Intelligent Health Management System. Academic Journal of Engineering and Technology Science (2024) Vol. 7, Issue 4: 161-169. https://doi.org/10.25236/AJETS.2024.070423.

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