Snowmotion A Wearable Sensor-based Mobile Platform For Alpine Skiing Motion Capture And Analysis

Alpine skiing is a popular and challenging sport that requires high-level skills and coordination. However, skiing training and coaching are often subjective and qualitative, relying on human observation and feedback. Existing skiing monitoring systems are limited by the accuracy, reliability, and usability of the sensors, data processing, and visualization methods. Therefore, we propose to develop a wearable sensor-based mobile platform for alpine skiing motion capture, analysis, and feedback. This platform uses various sensors to measure the skier's posture and movement, employ machine learning and intelligent algorithms to evaluate the data, and provide training assistance to the skier. PURPOSE: To develop a wearable sensor-based mobile platform for alpine skiing motion capture, providing real-time feedback and training assistance. METHODS: 1) As shown in upper left of figure 1, five wearable sensors are attached to the user’s leg and torso to capture the kinematics data of alpine skiing. 2) In upper right of figure 1, The sensor data is communicated to a mobile device via Bluetooth, quaternion conversion and GPS information is processed. 3) The skiing motion was visualized using 3D motion reconstruction and user interface and feedback mechanism is designed. RESULTS: This platform uses various sensors to measure the skier's posture and movement, employ intelligent algorithms to evaluate the data, and provide training assistance to the skier. The verification is shown in the lower half of figure 1. CONCLUSION: In this paper, SnowMotion, a wearable sensor-based mobile platform for alpine skiing motion capture, analysis, and feedback, is presented. Various sensors are used to measure the skier's posture and movement, intelligent algorithms are applied to evaluate the data, and real-time training assistance is provided to the skier through a mobile app. The National Natural Science Foundation of China (11932013)