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Related Experiment Video

Updated: Jan 22, 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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Inertial measurement unit-based pose estimation: Analyzing and reducing sensitivity to sensor placement and body

Rezvan Kianifar1, Vladimir Joukov1, Alexander Lee2

  • 1Electrical and Computer Engineering Department, University of Waterloo, Waterloo, ON, Canada.

Journal of Rehabilitation and Assistive Technologies Engineering
|June 28, 2019
PubMed
Summary

A simple calibration for inertial measurement units (IMUs) significantly improves lower body pose estimation accuracy during clinical mobility tests. This method enhances accuracy without complex procedures, making it practical for clinical use.

Keywords:
Inertial measurement unitcalibrationclinical applicationextended Kalman filterforward kinematicshuman pose estimationjoint anglemisorientationsensitivity analysis

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Area of Science:

  • Biomechanics
  • Clinical Biomechanics
  • Rehabilitation Engineering

Background:

  • Inertial measurement units (IMUs) offer potential for automated pose estimation and exercise monitoring in clinical settings.
  • Extensive calibration procedures in existing methods limit their clinical applicability.
  • Lower body pose estimation is crucial for assessing mobility during clinical tests.

Purpose of the Study:

  • To adapt an IMU-based pose estimation method for lower body mobility tests.
  • To investigate the sensitivity of pose estimation accuracy to kinematic and sensor parameters.
  • To develop a simplified calibration protocol for improved clinical application.

Main Methods:

  • Utilized an extended Kalman filter and kinematic chain modeling for lower body pose estimation.
  • Performed sensitivity analysis on kinematic model and sensor placement parameters.
  • Developed and applied a simple calibration protocol focusing on IMU orientation.

Main Results:

  • Sensitivity analysis identified IMU orientation as critical for accuracy.
  • The proposed simple calibration protocol significantly improved joint angle accuracy.
  • Ankle, knee, and hip joint angle errors were reduced without additional calibration.

Conclusions:

  • Pose estimation accuracy using body-worn IMUs depends on a limited set of parameters.
  • A straightforward calibration for IMU orientation yields effective pose estimation.
  • This approach enhances the clinical feasibility of IMU-based pose estimation.