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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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Inter-session repeatability of markerless motion capture gait kinematics.

Robert M Kanko1, Elise Laende1, W Scott Selbie2

  • 1Mechanical and Materials Engineering, Queen's University, Canada.

Journal of Biomechanics
|April 19, 2021
PubMed
Summary

Markerless motion capture reliably measures lower limb gait kinematics. This video-based approach offers practical benefits over traditional marker-based systems for clinical gait analysis.

Keywords:
Deep learningGait analysisKinematicsMarkerless motion captureRepeatability

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Area of Science:

  • Biomechanics
  • Human Movement Analysis
  • Motion Capture Technology

Background:

  • Marker-based motion capture is the standard for gait analysis but has limitations.
  • Markerless motion capture offers practical advantages for collecting gait kinematics.
  • Reliability of markerless systems is crucial for clinical adoption.

Purpose of the Study:

  • To assess the reliability of lower limb gait kinematics derived from markerless motion capture.
  • To compare markerless system reliability against established protocols for marker-based systems.
  • To determine the suitability of markerless motion capture for clinical gait analysis.

Main Methods:

  • Utilized an established reliability testing protocol with eight healthy adults.
  • Recorded over-ground walking trials using eight synchronized cameras.
  • Computed 3D lower limb joint angles from video-based pose estimates.

Main Results:

  • Inter-trial variability averaged 2.5° across joint angles, slightly higher than some marker-based studies.
  • Inter-session variability averaged 2.8°, demonstrating lower values than previously reported.
  • Variability ratios averaged 1.1, indicating minimal impact of multi-session protocols on total variability.

Conclusions:

  • Markerless motion capture provides reliable measurements of lower limb gait kinematics.
  • The system demonstrates practical benefits and potential for clinical application in gait analysis.
  • This technology advances the field of human movement analysis and clinical biomechanics.