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Related Experiment Video

Updated: May 25, 2026

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
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Published on: May 26, 2020

Upper limb joint angle tracking with inertial sensors.

Mahmoud El-Gohary1, Lars Holmstrom, Jessie Huisinga

  • 1Biomedical Signal Processing Laboartory, Department of Electrical and Computer Engineering at Portland State University, Portland, Oregon, USA. mahmoud@pdx.edu

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|January 19, 2012
PubMed
Summary

This study introduces a new method using wearable sensors and the unscented Kalman filter (UKF) to accurately track human joint movement. The technique shows high correlation with optical systems, improving physical activity and functional ability assessments.

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Area of Science:

  • Biomechanics
  • Wearable Technology
  • Robotics

Background:

  • Wearable inertial systems monitor human movement for insights into physical activity and function.
  • Traditional orientation tracking using gyroscopes suffers from drift errors.
  • Kalman filters (including EKF) are used to fuse accelerometer data and compensate for gyroscope drift.

Purpose of the Study:

  • To develop and validate a novel method for continuous estimation of human shoulder and elbow joint angles.
  • To leverage kinematic models from robotic arm control and the unscented Kalman filter (UKF) for improved motion tracking.
  • To demonstrate the generalizability of the methodology for tracking other human joints.

Main Methods:

  • Utilized two wearable sensors to capture movement data.
  • Combined robotic arm kinematic models with the unscented Kalman filter (UKF).
  • Estimated continuous angles of human shoulder and elbow joints.

Main Results:

  • Achieved continuous estimation of human shoulder and elbow joint angles.
  • Demonstrated high correlation (consistently > 0.9) with optical motion tracking systems.
  • Validated the accuracy and reliability of the proposed wearable sensing method.

Conclusions:

  • The developed methodology offers a robust approach for wearable human movement tracking.
  • The technique shows promise for enhancing assessments of physical activity and functional ability.
  • The method is adaptable for tracking various human joints, expanding its application potential.