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The Potential of Computer Vision-Based Marker-Less Human Motion Analysis for Rehabilitation.

Thomas Hellsten1, Jonny Karlsson2, Muhammed Shamsuzzaman2

  • 1Department of Health and Wellbeing, Arcada University of Applied Sciences, Helsinki, Finland.

Rehabilitation Process and Outcome
|January 6, 2022
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Marker-less human pose estimation shows promise for telerehabilitation, offering cost-effective and accessible motion analysis. Further validation is needed to ensure accuracy for widespread clinical adoption in rehabilitation.

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Computer visionmarker-lessmotion analysistelerehabilitation

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Area of Science:

  • Biomedical Engineering
  • Computer Vision
  • Rehabilitation Science

Background:

  • The aging population and the COVID-19 pandemic have increased demand for accessible telerehabilitation services.
  • Computer vision-based marker-less human pose estimation offers a promising, non-invasive approach for remote patient monitoring and exercise analysis.
  • Current challenges include achieving precise accuracy in joint identification and motion analysis for clinical applications.

Purpose of the Study:

  • To critically review recent computer vision-based marker-less human pose estimation systems.
  • To assess the applicability of these systems for rehabilitation.
  • To provide an overview of existing marker-less telerehabilitation applications.

Main Methods:

  • A critical review of recent marker-less human pose estimation systems was conducted.
  • Focus was placed on joint localization accuracy relative to physiotherapy standards and ease of use.
  • Knee angle measurement accuracy was analyzed via simulation.

Main Results:

  • Current systems utilize 2D, 3D, single, and multi-view techniques.
  • 3D marker-less pose estimation from a single view is most promising for physiotherapy, enabling advanced motion analysis with minimal equipment.
  • Preliminary simulations indicate sufficient accuracy for 2D joint angle estimations in some systems.

Conclusions:

  • Promising results exist for certain marker-less pose estimation techniques in rehabilitation applications.
  • More rigorous testing and validation are essential to confirm accuracy and reliability.
  • Widespread adoption in advanced telerehabilitation requires further evidence of performance.