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Updated: Oct 17, 2025

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
Development of a Low-Cost Open-Source Measurement System for Joint Angle Estimation.
Túlio Fernandes de Almeida1, Edgard Morya1, Abner Cardoso Rodrigues1
1Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba 59280-000, Brazil.
This study presents a low-cost, open-source system using inertial measurement units (IMUs) for joint angle estimation. The system demonstrates accurate joint angle measurement in laboratory and real-world scenarios, offering a viable alternative for motion analysis.
Area of Science:
- Biomechanics
- Wearable Technology
- Robotics
Background:
- Inertial Measurement Units (IMUs) offer a cost-effective method for measuring joint angles.
- Existing systems for joint angle estimation can be expensive and complex.
- Open-source solutions are needed to increase accessibility in research and clinical applications.
Purpose of the Study:
- To develop and validate a low-cost, open-source measurement system for joint angle estimation using IMUs.
- To assess the system's performance in controlled and real-world environments.
- To compare the system's software accuracy against gold-standard devices.
Main Methods:
- Hardware development using low-cost IMUs and microcontrollers.
- Software development in Python, incorporating Complementary, Kalman, and Madgwick fusion filters.
- Experimental validation involving a Lokomat robotic knee, a healthy adult during gait, and comparison with ground truth data.
Main Results:
- The system achieved an average range of motion (ROM) of 58.28° for the Lokomat knee.
- In a real-world gait scenario, the system recorded an average knee ROM of 44.62°.
- Software comparison with ground truth yielded a root-mean-square error of 0.04 and a mean average percentage error of 2.95%.
Conclusions:
- The developed low-cost, open-source IMU system provides accurate joint angle estimation.
- The system's modular hardware and versatile software filters demonstrate effectiveness in diverse scenarios.
- These findings support the system's potential application in various motion analysis contexts.
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