The Artificial Intelligence System for the Generation of Sports Education Guidance Model and Physical Fitness Evaluation Under Deep Learning
Bibliographic Data
| ID | 22074239 |
|---|---|
| Authors | Yuanqing Li (0000-0002-8283-7116, Henan University), Xiangliang Li (0000-0001-7608-5408, Shanghai Lixin University of Accounting and Finance, corresponding author) |
| Year | 2022 |
| Volume | 10 |
| Pages | 917053-917053 |
| Publication date | 2022-08-09 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2022.917053 |
| PMID | 36016903 |
| OpenAlex | W4290729774 |
| Language | EN |
| Citations received | 3 |
| References cited | 30 |
In recent years, China's achievements in artificial intelligence (AI) have attracted the attention of the world, and AI technology has penetrated into all walks of life. In particular, the in-depth integration of AI technology with sports education guidance and physical fitness evaluation has achieved very significant progress and results, which has improved the quality of life of people and provided more high-quality, customized, and personalized health management services for human beings. This study aimed to explore the application model of deep learning in sports education and guidance and in the analysis of the residents' physical fitness, so as to formulate a personalized and intelligent exercise program. The residents of A and B units are selected as the research object to evaluate the physical fitness. Subsequently, the self-designed questionnaire is used to survey the chronic disease online, and the acquired data are put into a deep learning model for the analysis to obtain the physique scoring results and exercise guidance. According to the results of physical fitness evaluation, the proportion of overweight was the highest (40.4%), followed by fatty liver (24.3%) and hyperlipidemia (20.4%), showing high incidence in people aged 41–50 years. The highest incidence of female gynecological diseases was gout (23.0%) and hyperlipidemia (20.6%). After exercise therapy, the scores were excellent and good. Conclusions: The database SQL Server 2005 was a platform for storing all kinds of data and knowledge-based rule information. The user's access service was provided by the remote server via the browser. Therefore, building a rule-based reasoning mechanism can realize physical test data collection, physical fitness evaluation, and information management for improving physical fitness
Big data · Data mining · Deep learning · Medical education · Multimedia · Obesity · Overweight · Pathology · Physical fitness · Physical therapy · Cardiovascular Health and Risk Factors · Computer Science · Medicine · Physical Activity and Health · Physical Education and Training Studies · Artificial Intelligence
Artificial intelligence in physical education
The role of artificial intelligence in enhancing sports education and public health in higher education
Associations between generative AI use frequency, technology acceptance, attitudes toward AI, and reported learning preference patterns among students in physical education classes
| Citations per year | 1.5 |
|---|---|
| Citation span | 2024 - 2026 (3) |
| Highly cited | No |