Building a model and doing empirical research on effective exercise training in conjunction with biomechanics

Article ID: 1382

Abstract

With the rapid advancements in sports science and athletic training, the integration of biomechanics and information technology has driven the development of innovative theories and practices in sports training. Traditional training methods, which lack a scientific foundation, are increasingly seen as ineffective. In contrast, the biomechanical-based sports training model proposed in this study offers a theoretical framework for precisely enhancing athletes’ performance. This model addresses several critical issues, including limited equipment adaptability, the lack of universal principles across various sports, and the challenge of tailoring training models to individual needs. To overcome these challenges, the study introduces a novel, biomechanical-based sports training model, validated through empirical research. The model is supported by a biomechanical data collection system built using multi-source sensor fusion technology, which ensures adaptability to complex training environments. This system gathers kinematic, kinetic, and electromyographic data from athletes during key activities such as double-legged downward longitudinal jumps and all-out acceleration runs. Devices like the VICON infrared camera system, a three-dimensional force measuring table, and a surface electromyography tester provide high-quality data essential for model development. Furthermore, the deep learning algorithm used in the model enhances the understanding of common principles across different sports. The model incorporates optimal designs for customized parameters to address various training needs. The empirical research employs a randomized controlled trial, dividing participants into experimental and control groups. After eight weeks of training, the model’s stability and applicability across different sports are confirmed. The experimental group’s training program is designed with a multi-phase approach, which includes injury prevention, targeted training, and recovery stretching, providing comprehensive support to athletes. The study’s findings show that the biomechanics-based sports training model significantly improves training effectiveness and fosters the integration of theoretical and practical aspects of competitive sports and sports science. This research serves as a crucial reference point for the future development of sports training models, highlighting the importance of scientific foundations in optimizing athletic performance.