Application of AI technology in muscle injury prevention in public sports basketball tests in colleges and universities
AI public sports teaching technology is applied to daily indoor or outdoor fixed sports tests, ability assessments, and sports classroom teaching scenarios. It provides automated voice broadcast guidance, sports video AI intelligent engine automatic analysis, real-time detection of illegal actions, and intelligent real-time output of sports test results; Through AI intelligent guidance, the whole process of basketball test sports analysis and training suggestions are realized, and students are encouraged to conduct self-evaluation, promote training through testing, and practice more frequently. It also promotes the normalization of sports testing/teaching in public physical education in colleges and universities through teaching demonstration video explanations and a combination of various classroom forms, accumulates campus physical test data, and assists public physical education teaching and testing in colleges and universities. AI technology has intelligent joint detection and marking, multi-subject tracking and recognition. It does not require any markers to be installed on the captured object, and can capture accurate motion through video. During the basketball test, if an abnormal situation occurs, the student needs to stop the test. AI technology uses motion capture and analysis systems to help students and teachers better understand the sports skills and techniques tested in basketball, thereby developing more effective sports teaching and training plans. Motion capture and analysis systems can be used to evaluate athletes’ gait and posture to help them improve their techniques and reduce the risk of injury.
Authors
- Qian‐Li Xue (ORCID: https://orcid.org/0000-0001-8818-7444)
- Sisi He (ORCID: https://orcid.org/0000-0002-1722-660X)
Institutions
- Hezhou University (CN)
Publication Details
- Journal
- Molecular & cellular biomechanics
- Published
- 2025-02-20
- DOI
- https://doi.org/10.62617/mcb1140
- Primary Topic
- E-commerce and Technology Innovations
- Type
- article
- Field-Weighted Citation Impact
- 0.00