Koshio, T.; Haraguchi, N.; Takahashi, T.; Hara, Y.; Hase, K. Estimation of Ground Reaction Forces during Sports Movements by Sensor Fusion from Inertial Measurement Units with 3D Forward Dynamics Model. Sensors2024, 24, 2706.
Koshio, T.; Haraguchi, N.; Takahashi, T.; Hara, Y.; Hase, K. Estimation of Ground Reaction Forces during Sports Movements by Sensor Fusion from Inertial Measurement Units with 3D Forward Dynamics Model. Sensors 2024, 24, 2706.
Koshio, T.; Haraguchi, N.; Takahashi, T.; Hara, Y.; Hase, K. Estimation of Ground Reaction Forces during Sports Movements by Sensor Fusion from Inertial Measurement Units with 3D Forward Dynamics Model. Sensors2024, 24, 2706.
Koshio, T.; Haraguchi, N.; Takahashi, T.; Hara, Y.; Hase, K. Estimation of Ground Reaction Forces during Sports Movements by Sensor Fusion from Inertial Measurement Units with 3D Forward Dynamics Model. Sensors 2024, 24, 2706.
Abstract
Rotational jumps are crucial techniques in sports competitions. Estimating ground reaction forces (GRFs), one of the components constituting jumps, through a biomechanical model-based approach enables analysis even in environments where force plates or machine learning training data cannot be utilized. In this study, rotational jump movements involving twists on land were measured using inertial measurement units (IMUs) and estimated GRFs and body loads using a 3D forward dynamics model. Our estimation method, based on forward dynamics and optimization calculations, generated and optimized body movements using cost functions defined by motion measurements and internal body loads. To reduce the influence of the dynamic acceleration in the optimization calculation, the 3D orientation using sensor fusion composed of acceleration and angular velocity data obtained from IMUs and an extended Kalman filter was estimated. As a result, by generating movements based on the cost function, it was possible to calculate biomechanically valid GRFs while following the measured movements even if not all joints are covered by IMUs. This estimation method allows for 3D motion analysis independent of measurement conditions or training data.
Copyright:
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