全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

Summary of the Research Status of Artificial Intelligence in Sports Performance Analysis of Athletes

DOI: 10.4236/oalib.1110539, PP. 1-7

Subject Areas: Sports Science

Keywords: Artificial Intelligence, Sports Performance, Smart Sports, Athletes

Full-Text   Cite this paper   Add to My Lib

Abstract

Using literature, logical analysis and other methods to systematically sort out and reflect on the domestic and foreign frontier research progress in the field of artificial intelligence to improve sports performance. It is found that the current research on artificial intelligence to improve sports performance mainly focuses on four aspects: the evaluation of athletes’ physical function status and sports posture, the analysis of winning rules, the regulation of pre-match mental state, and the prevention and treatment of sports injuries.

Cite this paper

Li, L. (2023). Summary of the Research Status of Artificial Intelligence in Sports Performance Analysis of Athletes. Open Access Library Journal, 10, e539. doi: http://dx.doi.org/10.4236/oalib.1110539.

References

[1]  Zheng, F. and Xu, W.K. (2019) Smart Sports in China: Research on Rise, Development and Countermeasures. Sports Science, 39, 14-24.
[2]  Fu, J. (2016) Design and Application of K-Line Diagram Monitoring and Expression Tools for Athletes’ Functional Status. Hunan University, Changsha.
[3]  Huang, Y., Qiu, Z.J., Li, J., Liang, S.X., Chen, X.B., Lin, G.K., Wang, Q. and Li, X.Z. (2003) The Development of a Real-Time Monitoring System for Athletes’ Functional Status. Sports Science, 23, 110-113.
[4]  Zhu, Q.Y. (2015) Technical Analysis of Body Movement Postures. Forest District Teaching, No. 7, 98-99.
[5]  Zhou, S. (2013) Research on the Winning Rules of Men’s Boxing Events in China. Beijing Sport University, Beijing.
[6]  Apham, A.C. and Bartlett, R.M. (1995) The Use of Artificial Intelligence in the Analysis of Sports Performance: A Review of Applications in Human Gait Analysis and Future Directions for Sports Biomechanics. Journal of Sports Sciences, 13, 229-237. https://doi.org/10.1080/02640419508732232
[7]  Mccabe, A. (2002) An Artificially Intelligent Sports Tipper. In: Mckay, B. and Slaney, J., Eds., AI2002: Advances in Artificial Intelligence, Springer, Berlin, 718. https://doi.org/10.1007/3-540-36187-1_67
[8]  Reed, D. and O’donoghue, P. (2005) Development and Application of Computer-Based Prediction Methods. International Journal of Performance Analysis in Sport, 5, 12-28. https://doi.org/10.1080/24748668.2005.11868334
[9]  Mccabe, A. and Trevathan, J. (2008) Artificial Intelligence in Sports Prediction. 5th International Conference on Information Technology: New Generations (ITNG 2008), Las Vegas, 7-9 April 2008, 1194-1197. https://doi.org/10.1109/ITNG.2008.203
[10]  Yin, Y.J. (2017) Development and Research of Sports Evaluation Decision Support System Based on Data Mining. Modern Electronic Technology, 40, 108-111.
[11]  Tian, M.J., Liu, J.H., et al. (2000) General Textbook for Physical Education Colleges. In: Sports Training, People’s Sports Publishing House, Beijing, 289.
[12]  Bailon, C., Damas, M., Pomares, H., et al. (2019) SPIRA: An Automatic System to Support Lower Limb Injury Assessment. Journal of Ambient Intelligence and Humanized Computing, 10, 2111-2123. https://doi.org/10.1007/s12652-018-0722-6
[13]  Takagi, H. (2012) Interactive Evolutionary Computation for Analyzing Human Awareness Mechanisms. Applied Computational Intelligence and Soft Computing, 2012, Article ID: 694836. https://doi.org/10.1155/2012/694836
[14]  Li, J.X., Wu, J.Y., Li, Y.J., et al. (2019) Mental Health Early Warning Technology Based on Internet Machine Learning. Electronic Technology and Software Engineering, No. 8, 148.
[15]  Qian, J.X. and Yu, J.Y. (2016) IRT-Based Quantum Genetic Algorithm Topic Selection Strategy. Psychological Science, 39, 796-800.
[16]  Wang, J.Y. (2021) Research on the Causes and Countermeasures of Sports Injuries of High School Physical Education Students. Zhengzhou University, Zhengzhou.
[17]  Albu, A. and Stanciu, L. (2015) Benefits of Using Artificial Intelligence in Medical Predictions. 2015 E-Health and Bioengineering Conference (EHB), Iasi, 19-21 November 2015, 1-4. https://doi.org/10.1109/EHB.2015.7391610
[18]  Tang, D.P. (2020) Hybridized Hierarchical Deep Convolutional Neural Network for Sports Rehabilitation Exercises. IEEE Access, 8, 118969-118977. https://doi.org/10.1109/ACCESS.2020.3005189
[19]  Zhuang, J., Sun, J.L. and Yuan, G.L. (2021) Arrhythmia Diagnosis of Young Martial Arts Athletes Based on Deep Learning for Smart Medical Care. Neural Computing and Applications, 35, 14641-14652. https://doi.org/10.1007/s00521-021-06159-4
[20]  Oliver, J.L., Ayala, F., de Ste Croix, M.B.A., et al. (2020) Using Machine Learning to Improve Our Understanding of Injury Risk and Prediction in Elite Male Youth Football Players. Journal of Science and Medicine in Sport, 23, 1044-1048. https://doi.org/10.1016/j.jsams.2020.04.021

Full-Text


comments powered by Disqus

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133

WeChat 1538708413