Abstract
Velocity-based training (VBT) is a scientifically grounded approach to resistance training that provides trainers with precise and reliable guidance by measuring the velocity of the barbell during exercise. Inertial measurement units (IMUs) possess advantages such as low cost and compact size. However, the use of IMUs to accurately estimate velocities and displacements requires refinement due to potential measurement errors. In this paper, we introduce an innovative IMU-based method for acquiring barbell velocity and displacement and conducting motion counting. This approach combines integration and high-pass filtering, allowing for the accurate acquisition of barbell mean concentric velocity (MV), peak concentric velocity (PV), and displacement for both back squat and bench press exercises. Furthermore, it enables precise motion counting. Five healthy male participants were enlisted for the test. The results demonstrated strong correlations between our method and the linear position transmitter (LPT). For back squat and bench press exercises, the Pearson’s product moment correlation coefficient (Pearson’s r) for MV was 0.93 and 0.91, the intra-class correlation (ICC) was 0.93 and 0.91, and the coefficient of variation (CV) was 13.29% and 16.22%, respectively. For PV, the Pearson’s r was 0.92 and 0.95, the ICC was 0.92 and 0.94, and the CV was 13.46% and 17.34%, respectively. These results further demonstrated the validity and reliability of the method proposed in this paper regarding resistance training guidance.
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The data used to support the findings of this study are available from the corresponding author upon request.
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Methodology: BCW, STZ, JFZ, JT; Hardware: JFZ, YJL, CBC; Data collection: JT, JFZ, MQF, STZ; Data analysis: STZ; Visualization: STZ; Writing - original draft: STZ; Writing - review & editing: CFY, BCW, YJL, JFZ, JT, MQF, CBC, STZ. All authors reviewed the manuscript.
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Zhang, S., Yang, C., Zhu, J. et al. A Method for Obtaining Barbell Velocity and Displacement and Motion Counting Based on IMU. Mobile Netw Appl (2024). https://doi.org/10.1007/s11036-024-02293-0
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DOI: https://doi.org/10.1007/s11036-024-02293-0