Integration of biomechanics and IoT in physical dance sports: Enhancing campus culture and psychological development in higher education

  • Lin Jiang Department of Physical Education, Henan Polytechnic Institute, Nanyang 473000, China
Keywords: biomechanics; Internet of Things; digital twin; sport dance; campus culture
Article ID: 1202

Abstract

Sports dance, a sport that combines art and competition, has steadily taken center stage in university physical education programs in recent years. This study examines the complex relationship between sports dancing, campus culture, and college students’ psychological development using digital twin technologies and the Internet of Things (IoT). In order to provide a thorough investigation of the physical movement features involved in sports dance, the emphasis is on introducing a biomechanical perspective. A connected model of the biomechanical properties and psychological development aspects of sports dance movements was built, and a hierarchical nearest neighbor propagation approach was suggested for multi-level pose clustering of sports dance motions. It was discovered through experimental validation that the digital twin-based dance scene design greatly increased dance motion capture accuracy and optimized the virtual digital scene for motion recovery. According to the study’s findings, biomechanical data analysis powered by digital twins can more effectively describe the kinematic and dynamic properties of dance moves and raise the level of scientificity in dance movement instruction and performance. Furthermore, the model’s stability is demonstrated by the optimized model’s split half reliability coefficient of 0.889 and internal consistency coefficient of 0.887. This study offers a novel method for the theoretical investigation and real-world implementation of sports dance instruction in higher education by fusing biomechanics and digital technology, which supports the enhancement of students’ mental and physical well-being.

References

1. Xie K, Zhang Peng. Influences of intelligent dance robots using the internet of things and human-computer interaction interfaces combined with psychological space construction on dance creativity. Journal of Computational Methods in Science and Engineering. 2024.

2. Atzori L, Iera A, Morabito G. The Internet of Things: A survey. Computer Networks. 2010; 54(15): 2787-2805. doi: 10.1016/j.comnet.2010.05.010

3. Kopetz H, Steiner W. Real-Time Systems. Springer International Publishing; 2022. doi: 10.1007/978-3-031-11992-7

4. Wang Z, Dong J. Design of Dance Data Management System Based on Computer-Aided Technology Under the Background of Internet of Things. Computer-Aided Design and Applications. Published online July 18, 2022: 45-55. doi: 10.14733/cadaps.2023.s2.45-55

5. Ray PP. A survey on Internet of Things architectures. Journal of King Saud University - Computer and Information Sciences. 2018; 30(3): 291-319. doi: 10.1016/j.jksuci.2016.10.003

6. Want R, Schilit BN, Jenson S. Enabling the Internet of Things. Computer. 2015; 48(1): 28-35. doi: 10.1109/mc.2015.12

7. El Saddik A. Digital Twins: The Convergence of Multimedia Technologies. IEEE MultiMedia. 2018; 25(2): 87-92. doi: 10.1109/mmul.2018.023121167

8. Zhou J, Sun J, Zhang W, et al. Multi-view underwater image enhancement method via embedded fusion mechanism. Engineering Applications of Artificial Intelligence. 2023; 121: 105946. doi: 10.1016/j.engappai.2023.105946

9. Zhou J, Pang L, Zhang D, et al. Underwater Image Enhancement Method via Multi-Interval Subhistogram Perspective Equalization. IEEE Journal of Oceanic Engineering. 2023; 48(2): 474-488. doi: 10.1109/joe.2022.3223733

10. Wei L, Wang SJ. Motion Tracking of Daily Living and Physical Activities in Health Care: Systematic Review from Designers’ Perspective. JMIR mHealth and uHealth. 2024; 12: e46282. doi: 10.2196/46282

11. Grygus I, Nesterchuk N, Hrytseniuk R, et al. Correction of posture disorders with sport and ballroom dancing. Medicni perspektivi (Medical perspectives). 2020; 25(1): 174-184. doi: 10.26641/2307-0404.2020.1.200418

12. Song Q. Interactive learning environment for the sporting skills development of physical education students. Education and Information Technologies. 2023; 29(10): 12597-12620. doi: 10.1007/s10639-023-12280-9

13. Pushkina N. Developing Social Skills Through Rhythmic Gymnastics in American sport. Futurity of Social Sciences. 2024; 2(2): 79-102. doi: 10.57125/fs.2024.06.20.05

14. Zhuoxiao Liu. Construction and Optimization of Sports Athlete Selection and Talent Cultivation System Based on Data Analysis. Journal of Electrical Systems. 2024; 20(6s): 2070-2081. doi: 10.52783/jes.3122

15. Alsalhi, Najeh Rajeh, et al. Analyzing the impact of sports education and psychological needs on kids’ educational outcomes-a machine learning approach. Revista de Psicologia del Deporte (Journal of Sport Psychology). 2023.

16. Medagedara MH, Ranasinghe A, Lalitharatne TD, et al. Advancements in Textile-Based sEMG Sensors for Muscle Fatigue Detection: A Journey from Material Evolution to Technological Integration. ACS Sensors. 2024; 9(9): 4380-4401. doi: 10.1021/acssensors.4c00604

17. Zhang M, Sun F, Wen Y, et al. A self-powered intelligent integrated sensing system for sports skill monitoring. Nanotechnology. 2023; 35(3): 035501. doi: 10.1088/1361-6528/ad0302

18. Zhang S, Lin X, Wan J, et al. Recent Progress in Wearable Self‐Powered Biomechanical Sensors: Mechanisms and Applications. Advanced Materials Technologies. 2024; 9(21). doi: 10.1002/admt.202301895

Published
2025-02-25
How to Cite
Jiang, L. (2025). Integration of biomechanics and IoT in physical dance sports: Enhancing campus culture and psychological development in higher education. Molecular & Cellular Biomechanics, 22(3), 1202. https://doi.org/10.62617/mcb1202
Section
Article