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