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Inertial measurement unit-based hip flexion test as an indicator of sprint performance.

Ryu NagaharaMai KamedaJonathon NevilleJean-Benoit Morin
Published in: Journal of sports sciences (2019)
This study aimed 1) to examine the validity of inertial measurement unit (IMU)-based hip flexion strength test, and 2) to investigate the hip flexion strength test as an indicator of sprint performance. Eight males performed five repeated hip flexion-extension, while leg motion was recorded using an IMU and a motion capture system (Mocap). As the second experiment, 24 male athletes performed the IMU-based hip flexion strength test and sprinted 50 m, during which step-to-step ground reaction force (GRF) was recorded. The strength test variables were calculated using IMU and Mocap data including angular impulse, mean moment, and positive and negative work and power. Using GRF data, step-to-step spatiotemporal variables were obtained. The results showed high intra-class correlation coefficient and correlation coefficient (both >0.909) between IMU and Mocap for angular impulse, mean moment, positive work and power. The hip flexion mean moment showed significant correlation with running speed from the 5th-8th step section onwards. The angular impulse, mean moment, positive work and power are recommended to be used for the IMU-based hip flexion strength test variables in terms of accuracy and validity. Moreover, the proposed IMU-based hip flexion strength test can be an indicator for better sprinting performance.
Keyphrases
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  • machine learning
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  • big data
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  • deep learning
  • artificial intelligence