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Updated: Jun 22, 2025
06:52
An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
Published on: May 26, 2020
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JointTracker: Real-time inertial kinematic chain tracking with joint position estimation.
Bertram Taetz1,2, Michael Lorenz1, Markus Miezal1
1Augmented Vision, German Research Center for Artificial Intelligence, Kaiserslautern, Rhineland-Palatinate, 67663, Germany.
Open Research Europe
|July 2, 2024
Summary
This study introduces calibration-free inertial motion capture, enabling accurate online estimation of sensor poses and human skeleton joint positions without prior setup. This advances in-field motion analysis for diverse applications.
Area of Science:
- Biomechanics
- Robotics
- Sensor Technology
Background:
- In-field human motion capture (HMC) is gaining traction, with camera-based markerless systems facing limitations like restricted fields of view and occlusions.
- Inertial motion capture offers an occlusion-free alternative for motion tracking outside laboratory settings, but requires spatial registration (sensor calibration).
Purpose of the Study:
- To develop a calibration-free approach for inertial motion capture.
- To enable simultaneous online estimation of sensor poses and joint positions for kinematic chains, such as the human skeleton.
Main Methods:
- Proposes a recursive estimator for simultaneous online estimation of sensor poses and joint positions.
- Derivation from an optimization objective is provided.
- Applicable to synchronized data streams from body-mounted inertial sensor networks.
Main Results:
- Demonstrates successful evaluations on noisy simulated data from a three-link chain.
- Validated on real lower-body walking data from 25 healthy individuals.
- Tested with walking data from a humanoid robot.
Conclusions:
- The proposed method enables calibration-free inertial motion capture.
- Facilitates accurate online estimation of human skeleton kinematics.
- Offers a robust solution for in-field motion analysis and human-robot interaction.
Keywords:
3D human pose estimation3D kinematicscalibration-freeinertial motion captureonline joint position estimationparameter estimationrecursive state estimationMore Related Videos
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