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Comparison of computational pose estimation models for joint angles with 3D motion capture.

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Summary

Two pose estimation models, HRNet and MediaPipe, show reliable joint angle and range of motion (ROM) calculations for human movement analysis in rehabilitation. Both models offer valuable, consistent data comparable to marker-based systems.

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Area of Science:

  • Biomechanics
  • Human Movement Analysis
  • Rehabilitation Technology

Background:

  • Musculoskeletal clinicians and researchers require accurate human movement analysis tools for effective rehabilitation assessments.
  • Objective quantification of joint angles and range of motion (ROM) is crucial for evaluating movement patterns.

Purpose of the Study:

  • To compare the accuracy of two human pose estimation models, HRNet and MediaPipe, against a laboratory marker-based reference system.
  • To evaluate the reliability of these models for calculating joint angles and ROM during various movements.

Main Methods:

  • Twenty-two healthy volunteers performed five distinct movements.
  • Joint angles and ROM were calculated using the HRNet and MediaPipe models and compared to Qualisys Track Manager (marker-based system).
  • Coefficient of Variation (CoV) and Intra-class Correlation Coefficients (ICCs) were used for statistical analysis.

Main Results:

  • Both HRNet and MediaPipe demonstrated reliable joint angle calculations with CoV values under 10% across all tested activities.
  • ROM comparisons showed low CoV, with good-excellent ICCs for most exercises, except for the left knee during sit-to-stand.
  • Flexion/extension movements yielded more consistent results than sit-to-stand movements when compared to 3D motion analysis.

Conclusions:

  • HRNet and MediaPipe provide reliable and comparable kinematic data for human movement analysis in a clinical rehabilitation setting.
  • These models offer a valuable alternative for objective movement analysis where advanced motion capture systems are unavailable.
  • Further model refinement can enhance reliability for more complex movement analyses.