Research on Position Layout Strategy of Posture Sensors in Alpine Skiing Movement Analysis

This paper mainly studies the optimal layout strategy of posture sensors on the athlete's body position in the movement analysis of alpine skiing. This layout needs to satisfy the integrity of the collected movement data and streamline the number of sensors loaded by the athlete as much as possible. By comparing the current research status in this field, the paper simplifies the athlete's human body into a 17-node model. On this basis, by analyzing the correlation between the positions of the sensors and the technical characteristics of alpine skiing, the final conclusion is that it is enough to wear the posture sensors at the 8 joint positions of the athlete's body. It should be noted that the movement data comes from the indoor simulated alpine skiing training platform. In order to verify whether these 8 sensors can completely reconstruct the movement posture, this paper compares the motion reconstruction performance of the partial least squares method and the BP neural network algorithm, and obtains the final conclusion: the sensor layout strategy designed in this paper is effective, and the effect of the BP neural network algorithm is sufficient to meet the requirements of the experiment.