Development of a virtual simulation training platform for physical education teaching posture integrating biomechanics
Abstract
The development of an immersive virtual simulation training platform designed to enhance physical education by integrating biomechanics for precise posture training. Through the use of biomechanical analysis and virtual reality (VR), the platform offers real-time feedback and assessment, helping students to comprehend and correct their posture while engaging in physical activities. The research introduced an Improved Aquila Optimized Efficient Deep Convolution Neural Network (IAO-EDCNN) model to estimate joint kinematics and strength metrics, which are crucial for posture accuracy and injury prevention. To collect data from VR-compatible sensors to gather motion data continuously while users perform various physical exercises. The data was preprocessed using a Gaussian Filter to smooth data and reduce high-frequency noise in the data. Frequency-domain characteristics were extracted using the Fast Fourier Transform (FFT) as dominant frequency components of motion. IAO model ensures that the joint angles and positions during exercises are optimal and EDCNN can be employed to analyze motion capture data, assess joint kinematics, and predict strength metrics. The results indicate that upper-body kinematics can be accurately estimated with less error for joint angles, allowing for reliable real-time feedback during sessions. In a comparative analysis, the suggested method is assessed with various evaluation measures, such as F1-score (95.60%), recall (95.35%), precision (96.10%), and accuracy (95.85%). The result demonstrated the IAO-EDCNN method to estimate joint kinematics and strength metrics, which are crucial for posture accuracy and injury prevention. This innovative approach demonstrates that VR technology, paired with biomechanics can serve as an effective tool for posture training in physical education. By providing accessible, evidence-based metrics, this platform aims to enhance the quality of physical education through immersive and engaging training experiences.
References
1. Shan, S. and Sun, S., 2023, January. Design and Implementation of a Virtual Simulation Teaching Platform of Sports Action Technology Based on Maya. In International Conference on Innovative Computing (pp. 464-470). Singapore: Springer Nature Singapore. 10.1007/978-981-99-2092-1_59
2. Martay, J.L., Martay, H. and Carpes, F.P., 2021. BodyWorks: interactive interdisciplinary online teaching tools for biomechanics and physiology teaching. Advances in Physiology Education, 45(4), pp.715-719. 10.1152/advan.00069.2021
3. Klochko, O.V., Fedorets, V.M., Shyshkina, M.P., Branitska, T.R. and Kravets, N.P., 2020. Using the augmented/virtual reality technologies to improve the health-preserving competence of a physical education teacher. AET, 2022, p.726.
4. Xiao, H., Ren, J., Ling, H., Jiang, C. and Wang, P., 2023. Virtual Simulation-Based Study on Sports Anatomy: Technological Applications and Future Development. American Journal of Sports Science, 11(4), pp.84-89. 10.11648/j.ajss.20231104.11
5. Bores-García, D., Cano-de-la-Cuerda, R., Espada, M., Romero-Parra, N., Fernández-Vázquez, D., Delfa-De-La-Morena, J.M., Navarro-López, V. and Palacios-Ceña, D., 2024. Educational Research on the Use of Virtual Reality Combined with a Practice Teaching Style in Physical Education: A Qualitative Study from the Perspective of Researchers. Education Sciences, 14(3), p.291. 10.3390/educsci14030291
6. Yevtuch, M., Fedorets, V., Klochko, O., Shyshkina, M.P. and Dobryden, A.V., 2021. Development of the health-preserving competence of a physical education teacher on the basis of N. Bernstein's theory of movements construction using virtual reality technologies. In Proceedings of the 4th International Workshop on Augmented Reality in Education (AREdu 2021) Kryvyi Rih, Ukraine, May 11, 2021 (Vol. 2898, pp. 294-314). CEUR Workshop Proceedings.
7. Mishra, N., Habal, B.G.M., Garcia, P.S. and Garcia, M.B., 2024, June. Harnessing an AI-Driven Analytics Model to Optimize Training and Treatment in Physical Education for Sports Injury Prevention. In Proceedings of the 2024 8th International Conference on Education and Multimedia Technology (pp. 309-315).
8. Hu, W. and Liu, Y., 2024. Evaluation Model of the Teaching Effect of College Physical Education Class Based on Multimedia Feature Extraction Technology and Three-Dimensional Recons. International Journal of e-Collaboration (IJeC), 20(1), pp.1-20. 10.4018/IJeC.346379
9. Lin, J. and Song, J., 2023. Design of motion capture system in physical education teaching based on machine vision. Soft Computing, pp.1-10. 10.1007/s00500-023-08779-5
10. Li, C., Cao, Y. and Lv, J., 2024. Design and Implementation of a Physical Education Teaching and Training Mode Management System. Entertainment Computing, 50, p.100684. https://doi.org/10.1016/j.entcom.2024.100684
11. Boujdi, R., Rouani, A., Elouakfaoui, A., Lamri, D. and Ibrahimi, A., 2023. The effectiveness of a physical education teaching intervention based on biomechanical modeling on anaerobic power and sprint running performance of youth male students with deficit force profile. International Journal of Chemical and Biochemical Sciences, 24, pp.423-434.
12. Ma, Q. and Huo, P., 2022. Simulation analysis of sports training process optimisation based on motion biomechanical analysis. International Journal of Nanotechnology, 19(6-11), pp.999-1015. 10.1504/IJNT.2022.128982
13. Saklani, A., 2023. Integrating technology into physical education: Exploring the dynamics of AI, virtual reality, apps, and wearables for an enhanced educational odyssey.
14. Hou, Y. and Ouyang, B., 2023. Analysis of the enhancement of computer simulation on physical education teaching in colleges and universities. Applied Mathematics and Nonlinear Sciences, 9(1). 10.2478/amns-2024-0864
15. Chen, Y., 2021. Research on college physical education model based on virtual crowd simulation and digital media. Journal of Intelligent & Fuzzy Systems, 40(4), pp.7195-7207. 10.3233/JIFS-189547
16. Akanmu, A.A., Olayiwola, J., Ogunseiju, O. and McFeeters, D., 2020. Cyber-physical postural training system for construction workers. Automation in construction, 117, p.103272. 10.1016/j.autcon.2020.103272
17. Fernández-Vázquez, D., Navarro-López, V., Cano-de-la-Cuerda, R., Palacios-Ceña, D., Espada, M., Bores-García, D., Delfa-de-la-Morena, J.M. and Romero-Parra, N., 2024. Influence of Virtual Reality and Gamification Combined with Practice Teaching Style in Physical Education on Motor Skills and Students’ Perceived Effort: A Mixed-Method Intervention Study. Sustainability, 16(4), p.1584. 10.3390/su16041584
18. Lai, S., 2023. Optimization of Innovative Path of Physical Education Teaching in Colleges and Universities under Information Integration Technology. Applied Mathematics and Nonlinear Sciences, 9(1). 10.2478/amns-2024-0767
19. Yuan, Y., 2024. Exploration of Teaching and Training Methods for Track and Field Sports in School Physical Education. Journal of Human Movement Science, 5(2), pp.9-15. 10.23977/jhms.2024.050202
20. Jiang, Z., 2024. The Synergistic Effect of Biomechanics and Psychological Feedback in Physical Education Teaching: Enhancing Motor Skills and Psychological Resilience. Molecular & Cellular Biomechanics, 21(2), pp.447-447. 10.62617/mcb.v21i2.447
21. Xie, M., 2021. Design of a physical education training system based on an intelligent vision. Computer Applications in Engineering Education, 29(3), pp.590-602. 10.1002/cae.22259
22. Xiao, L., 2023. Virtual Simulation Based Experimental Sports Teaching Reform and Exploration. Adult and Higher Education, 5(2), pp.67-70. 10.23977/aduhe.2023.050213
23. Zhai, S., 2024, August. Innovative Practice of Online Teaching Model for College Physical Education Courses Empowered by Information Technology Education. In 2024 5th International Conference on Education, Knowledge and Information Management (ICEKIM 2024) (pp. 1146-1153). Atlantis Press. 10.2991/978-94-6463-502-7_123
24. Niu, X., 2022. Application Analysis of Sports Biomechanics in Physical Education and Training.
25. Ding, Y., Li, Y. and Cheng, L., 2020. Application of Internet of Things and virtual reality technology in college physical education. Ieee Access, 8, pp.96065-96074. 10.1109/ACCESS.2020.2992283
26. Mokmin, N.A.M., 2020. The effectiveness of a personalized virtual fitness trainer in teaching physical education by applying the artificial intelligent algorithm. International Journal of Human Movement and Sports Sciences, 8(5), pp.258-264. 10.13189/saj.2020.080514
27. ZhaoriGetu, H. and Li, C., 2024. Innovation in physical education teaching based on biomechanics feedback: Design and evaluation of personalized training programs. Molecular & Cellular Biomechanics, 21(2), pp.403-403. https://doi.org/10.62617/mcb403
28. Radwan, N.L., Mahmoud, W.S., Mohamed, R.A. and Ibrahim, M.M., 2021. Effect of adding plyometric training to physical education sessions on specific biomechanical parameters in primary school girls. Journal of Musculoskeletal & Neuronal Interactions, 21(2), p.237.
29. Hu, L., Liu, C., Cengiz, K. and Nallappan, G., 2021. Application of Internet of Things framework in physical education system. Journal of Internet Technology, 22(6), pp.1409-1418.
30. Liang, R., 2023. Research on the Path of Enhancing Physical Education Teaching in Colleges and Universities Based on the Background of Deep Learning. Applied Mathematics and Nonlinear Sciences. 10.2478/amns.2023.2.01274
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