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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.

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Summary
This summary is machine-generated.

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.

Keywords:
accelerometerssensor fusionsensors in healthcare

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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.