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SnowMotion: A Wearable Sensor-Based Mobile Platform for Alpine Skiing Technique Assistance.

Weidi Tang1, Xiang Suo2, Xi Wang1

  • 1Key Laboratory of Exercise and Health Sciences of Ministry of Education, Shanghai University of Sport, Shanghai 200438, China.

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|June 27, 2024
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Summary

SnowMotion is a new digital platform using wearable sensors for real-time skiing motion analysis. It enhances training by providing accurate feedback to improve skier performance and technique.

Keywords:
data visualizationdigital humanmobile applicationmotion capturewearable sensors

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Area of Science:

  • Biomechanics
  • Sports Technology
  • Human Motion Analysis

Background:

  • Improving skiing technique and performance is essential for athletes and enthusiasts.
  • Current motion monitoring methods face challenges in reliability, real-time analysis, usability, and cost.

Purpose of the Study:

  • To introduce SnowMotion, a digital human motion training assistance platform for skiing.
  • To overcome limitations of existing motion monitoring techniques in skiing.

Main Methods:

  • Utilized wearable sensors at five key body positions for high-precision kinematic data.
  • Developed the SnowMotion app for real-time data processing and analysis.
  • Generated a digital human image to reproduce skiing motion.

Main Results:

  • Achieved high motion capture accuracy (correlation coefficient > 0.95) and reliability compared to the Vicon system.
  • Demonstrated low mean error (5.033) and root-mean-square error (<12.50) for typical skiing movements.

Conclusions:

  • SnowMotion offers innovative solutions for technical advancement and training in alpine skiing.
  • Enables detailed movement analysis, deficiency identification, and targeted training plan development.
  • Expected to boost the popularization, training, and competition of alpine skiing.