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: 書貢獻/報告類型會議論文篇章

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%.

原文英語
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
出版狀態已發佈 - 2020 十二月
事件1st International Conference on Pervasive Artificial Intelligence, ICPAI 2020 - Taipei, 臺灣
持續時間: 2020 十二月 32020 十二月 5

出版系列

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

會議

會議1st International Conference on Pervasive Artificial Intelligence, ICPAI 2020
國家/地區臺灣
城市Taipei
期間2020/12/032020/12/05

ASJC Scopus subject areas

  • 人工智慧
  • 電腦科學應用
  • 決策科學(雜項)
  • 航空工程
  • 工業與製造工程
  • 控制和優化

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