Optimization of alpine skiing turning techniques based on biomechanics
Abstract
Alpine skiing turning technique requires high coordination of movements, but the existing training methods lack in-depth analysis of biomechanical characteristics. Athletes are prone to injuries during training. Technical optimization mainly relies on summarizing experience and lacks a precise quantitative basis. This paper aims to systematically analyze and optimize alpine skiing turning techniques from a biomechanical perspective, build a scientific action model and data analysis system, realize quantitative evaluation of technical movements, improve training safety and technical level, and provide scientific guidance for athletes. The study uses motion capture equipment to record three-dimensional motion trajectories and pressure sensors to collect mechanical data. By building an analysis model based on biomechanics, key features such as joint angles and torque changes are extracted, and an optimization scheme is designed in combination with a nonlinear multi-objective optimization algorithm. Based on these models and algorithms, a real-time feedback system is developed to provide personalized training suggestions to support athletes in adjusting movements and improving their technical level. The experimental results show that compared with the traditional training method, the coordination and balance of the optimized training model are improved by about 23.6% and 13.6% respectively, the action efficiency is improved by about 26.9%, and the risk of injury is reduced by more than 20%. In addition, the results of the model generalization ability test also show that the optimized training method has the characteristics of adapting to different groups. This shows that the optimized training method can significantly improve movement coordination and efficiency while reducing the risk of sports injuries, providing a new path for the scientific training of alpine skiing.
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