A Machine Learning-Based Countermovement Performance Measurement Method Using a Wearable IMU

Yi Yu Chiang, Wen Yueh Shih, Wei Han Chen, Jiun Long Huang, Tzyy Yuang Shiang

研究成果: Conference contribution同行評審

摘要

In the field of sports, there are many advanced technologies to help athletes improving their skills or monitoring their body health. The force plate is one of the devices which can be used to observe the status in neuromuscular function and fatigue of athletes by (1) asking them do the countermovement jump (CMJ) on it and (2) evaluating some performance indicators such as flight time and net pulse. However, the force plate is of low portability due to it high price and heavy weight. In this paper, we propose a machine learning-based method to measure CMJ performance with an inexpensive wearable inertial measurement unit (IMU). Based on the measured acceleration, we first extract some features and then adopt the machine learning algorithm to learn several models to estimate the above indicators, respectively. The experiments are conducted by 280 countermovement jumps performed by 14 healthy subjects. The experimental results show that the proposed system is of error rate less than 8%.

原文English
主出版物標題Proceedings - 2020 International Conference on Pervasive Artificial Intelligence, ICPAI 2020
發行者Institute of Electrical and Electronics Engineers Inc.
頁面79-85
頁數7
ISBN(電子)9780738142623
DOIs
出版狀態Published - 十二月 2020
事件1st International Conference on Pervasive Artificial Intelligence, ICPAI 2020 - Taipei, Taiwan
持續時間: 3 十二月 20205 十二月 2020

出版系列

名字Proceedings - 2020 International Conference on Pervasive Artificial Intelligence, ICPAI 2020

Conference

Conference1st International Conference on Pervasive Artificial Intelligence, ICPAI 2020
國家/地區Taiwan
城市Taipei
期間3/12/205/12/20

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