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An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
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Robust Plug-and-Play Joint Axis Estimation Using Inertial Sensors.

Fredrik Olsson1, Manon Kok2, Thomas Seel3

  • 1Systems and Control, Department of Information Technology, Uppsala University, SE-75105 Uppsala, Sweden.

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Summary
This summary is machine-generated.

This study introduces a plug-and-play inertial motion capture calibration method. It accurately estimates joint axes from motion data, eliminating the need for specific calibration phases.

Keywords:
gyroscopes and accelerometersinertial measurement unitsjoint axis identificationkinematic constraintssensor-to-segment calibrationvalidation on mechanical joint

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Area of Science:

  • Biomechanics
  • Robotics
  • Sensor Technology

Background:

  • Accurate sensor-to-segment calibration is crucial for inertial motion capture.
  • Existing methods require specific, informative motion within initial time windows and lack success indication.
  • Hinge joint axis identification is essential for applications like human movement analysis and robotics.

Purpose of the Study:

  • To develop a plug-and-play calibration method for inertial motion capture.
  • To enable accurate joint axis estimation from arbitrary motion data, overcoming limitations of current techniques.
  • To provide users with a clear indication of calibration success and accuracy.

Main Methods:

  • A novel method combining acceleration and angular rate data for globally optimal joint axis estimation.
  • Advanced sample selection techniques to identify informative data from larger datasets, discarding redundant measurements.
  • Uncertainty quantification to validate the accuracy and reliability of the estimated joint axis parameters.

Main Results:

  • Achieved angular errors of approximately 2 degrees using a selected subset of 125-1000 samples.
  • Demonstrated successful calibration using a mechanical joint across a wide range of motions.
  • Validated the method's ability to extract informative data even with non-ideal user movements.

Conclusions:

  • The proposed method offers the first truly plug-and-play solution for inertial motion capture joint axis calibration.
  • It eliminates the need for dedicated calibration phases, providing accurate estimates rapidly.
  • The method enhances usability by not requiring specific user motions and assuring calibration validity.