Abstract
In order to explore the relationship between sports and health and improve the scientific nature of sports, this paper uses cluster analysis algorithm as the basis, adopts the entropy estimation method for small sample sets to estimate the information entropy value, and improves the mutual information estimation to propose a mutual information estimation method based on entropy estimation. Moreover, this paper uses a clustering algorithm to combine sports and health intelligent diagnosis requirements to construct a system structure. The system recommends better sports suggestions to the user according to the user’s physical condition, makes sports plans according to the user’s health, and can also analyze the user’s sports process. In addition, on the basis of demand analysis, this paper designs experiments to test the performance of the system constructed in this paper. From the experimental statistical results, it can be seen that the system constructed in this paper can basically meet the actual needs of sports and health intelligent diagnosis. At the same time, this paper proves that there is a strong correlation between sports and health.
Highlights
In the modern city, people’s physical labor is less and less and mental work and work pressure are more and more, so people’s physical function according to the current mode of life is gradually declining. erefore, the defense ability of the whole body should be improved through sports, including muscle, bone, and the whole internal organs system and body circulation system. erefore, it is necessary to study the benefits of aerobic metabolism sports on menopausal women health.Exercise therapy is the application of sports in medicine
Personal errors or unreasonable sports are harmful to the physical condition but may aggravate some health risks. e analysis of the combination of basic personal body data and sports data to provide users with suitable health plans and sports programs and to guide people to perform more reasonable fitness will help our body’s health and disease prevention. is article combines the clustering analysis algorithm to construct a sports and health intelligent diagnosis system based on the clustering algorithm, sets the functional modules of the health diagnosis system based on actual needs, and verifies the performance of the system
Data Availability e labeled dataset used to support the findings of this study is available from the corresponding author upon request
Summary
People’s physical labor is less and less and mental work and work pressure are more and more, so people’s physical function according to the current mode of life is gradually declining. erefore, the defense ability of the whole body should be improved through sports, including muscle, bone, and the whole internal organs system and body circulation system. erefore, it is necessary to study the benefits of aerobic metabolism sports on menopausal women health. Exercise therapy is the application of sports in medicine It is a treatment method based on kinematics, biomechanics, and neurodevelopment, and its main goal is to improve the physical, physiological, psychological, and spiritual dysfunction, and its main factor is force and reaction. Exercise therapy includes both active physical activity training and passive physical activity training, and its functions include improving blood circulation, metabolism, and nerve control of sports tissues (muscles, bones, joints, and ligaments), promoting neuromuscular function, improving muscle strength, endurance, cardiopulmonary function, and balance function, and alleviating abnormalities [1]. Based on the above analysis and clustering analysis algorithm, this paper constructs an intelligent diagnosis system of motion and health based on cluster analysis, studies the relationship between motion and health, and verifies the performance of the system
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.