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Related Experiment Video

Updated: May 22, 2026

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
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Pronation-Supination Standardization Using a Data-Driven Statistical Pose Model.

Paul-Emmanuel Edeline1,2, Basile Longo3,4, Aziliz Guezou-Philippe3,5

  • 1LaTIM, INSERM U1101, Brest, France. paul-emmanuel.edeline@imt-atlantique.fr.

Journal of Imaging Informatics in Medicine
|May 20, 2026
PubMed
Summary

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This summary is machine-generated.

Forearm pronation-supination (PS) is better modeled using coupled radius-ulna pose modes than fixed-axis rotation. This data-driven approach enables computer-assisted PS standardization (CAPSS) for accurate 3D morphometric analysis without calibration.

Area of Science:

  • Orthopedics
  • Medical Imaging
  • Biomechanical Engineering

Background:

  • Image-based clinical forearm measurements can be inaccurate due to unaddressed pronation-supination (PS) during surgical repositioning.
  • Accurate accounting for forearm PS is crucial for reliable 3D morphometric analysis and surgical planning.

Purpose of the Study:

  • To develop and validate a data-driven joint statistical pose model (SPM) for the forearm, integrating both radius and ulna.
  • To support a linear angle-to-pose model for computer-assisted PS standardization (CAPSS).
  • To improve the accuracy of forearm pose estimation in clinical and research settings.

Main Methods:

  • An SPM was constructed from 88 forearm CT scans using principal component analysis (PCA) on coupled radius-ulna poses.
Keywords:
CT-based measurement standardizationComputational surgeryDistal radiusForearm kinematicsPronation-supinationStatistical pose model (SPM)

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Last Updated: May 22, 2026

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  • The SPM was fitted to 25 PS sweeps from cadaveric specimens with optical tracking.
  • Performance was compared against a fixed-axis rotation baseline using translational error (TE), rotational error (RE), and mesh RMSE.

    • Main Results:

    • The SPM accurately reproduced cadaveric PS trajectories with significantly lower errors (0.12 mm RMSE, 0.12 mm TE, 0.08° RE) compared to the baseline (2.5 mm RMSE, 1.9 mm TE, 5.3° RE).
    • A linear angle-to-pose model derived from PS-related SPM modes reconstructed unseen data with 1.9 mm RMSE, 1.6 mm TE, and 1.0° RE.
    • Forearm PS is effectively represented as coupled radius-ulna pose modes, outperforming single fixed-axis rotation models.

    Conclusions:

    • A data-driven joint statistical pose model effectively captures forearm pronation-supination as coupled radius-ulna movements.
    • The derived linear angle-to-pose model enables automated, calibration-free computer-assisted PS standardization (CAPSS).
    • This approach shows feasibility for pose-consistent 3D morphometric analysis, with further validation needed for pathological anatomy and surgical planning.