A Smart Ski Pole for Skiing Pattern Recognition and Quantification Application

Yangyanhao Guo; Renjie Ju; Kunru Li; Zhiqiang Lan; Lixin Niu; Xiaojuan Hou; Shuo Qian; Wei Chen; Xinyu Liu; Gang Li; Jian He; Xiujian Chou

doi:10.3390/s24165291

Sensors (Aug 2024)

A Smart Ski Pole for Skiing Pattern Recognition and Quantification Application

Yangyanhao Guo,
Renjie Ju,
Kunru Li,
Zhiqiang Lan,
Lixin Niu,
Xiaojuan Hou,
Shuo Qian,
Wei Chen,
Xinyu Liu,
Gang Li,
Jian He,
Xiujian Chou

Affiliations

Yangyanhao Guo: Science and Technology on Electronic Test and Measurement Laboratory, School of Instrument and Electronics, North University of China, Taiyuan 030051, China
Renjie Ju: Science and Technology on Electronic Test and Measurement Laboratory, School of Instrument and Electronics, North University of China, Taiyuan 030051, China
Kunru Li: Science and Technology on Electronic Test and Measurement Laboratory, School of Instrument and Electronics, North University of China, Taiyuan 030051, China
Zhiqiang Lan: School of Future Science and Engineering, Soochow University, Suzhou 215299, China
Lixin Niu: Science and Technology on Electronic Test and Measurement Laboratory, School of Instrument and Electronics, North University of China, Taiyuan 030051, China
Xiaojuan Hou: Science and Technology on Electronic Test and Measurement Laboratory, School of Instrument and Electronics, North University of China, Taiyuan 030051, China
Shuo Qian: School of Software, North University of China, Taiyuan 030051, China
Wei Chen: Science and Technology on Electronic Test and Measurement Laboratory, School of Instrument and Electronics, North University of China, Taiyuan 030051, China
Xinyu Liu: Science and Technology on Electronic Test and Measurement Laboratory, School of Instrument and Electronics, North University of China, Taiyuan 030051, China
Gang Li: School of Physical Education, Tianjin University of Sport, Tianjin 301600, China
Jian He: Science and Technology on Electronic Test and Measurement Laboratory, School of Instrument and Electronics, North University of China, Taiyuan 030051, China
Xiujian Chou: Science and Technology on Electronic Test and Measurement Laboratory, School of Instrument and Electronics, North University of China, Taiyuan 030051, China

DOI: https://doi.org/10.3390/s24165291
Journal volume & issue: Vol. 24, no. 16
p. 5291

Abstract

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In cross-country skiing, ski poles play a crucial role in technique, propulsion, and overall performance. The kinematic parameters of ski poles can provide valuable information about the skier’s technique, which is of great significance for coaches and athletes seeking to improve their skiing performance. In this work, a new smart ski pole is proposed, which combines the uniaxial load cell and the inertial measurement unit (IMU), aiming to provide comprehensive data measurement functions more easily and to play an auxiliary role in training. The ski pole can collect data directly related to skiing technical actions, such as the skier’s pole force, pole angle, inertia data, etc., and the system’s design, based on wireless transmission, makes the system more convenient to provide comprehensive data acquisition functions, in order to achieve a more simple and efficient use experience. In this experiment, the characteristic data obtained from the ski poles during the Double Poling of three skiers were extracted and the sample t-test was conducted. The results showed that the three skiers had significant differences in pole force, pole angle, and pole time. Spearman correlation analysis was used to analyze the sports data of the people with good performance, and the results showed that the pole force and speed (r = 0.71) and pole support angle (r = 0.76) were significantly correlated. In addition, this study adopted the commonly used inertial sensor data for action recognition, combined with the load cell data as the input of the ski technical action recognition algorithm, and the recognition accuracy of five kinds of cross-country skiing technical actions (Diagonal Stride (DS), Double Poling (DP), Kick Double Poling (KDP), Two-stroke Glide (G2) and Five-stroke Glide (G5)) reached 99.5%, and the accuracy was significantly improved compared with similar recognition systems. Therefore, the equipment is expected to be a valuable training tool for coaches and athletes, helping them to better understand and improve their ski maneuver technique.

Published in Sensors

ISSN: 1424-8220 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Technology: Chemical technology
Website: http://www.mdpi.com/journal/sensors

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