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Between-Day Reliability of Kinematic Variables Using Markerless Motion Capture for Single-Leg Squat and Single-Leg

Matias Yoma1,2, Lee Herrington2, Chelsea Starbuck3

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Markerless motion capture demonstrates reliable biomechanical data collection for single-leg tasks, comparable to marker-based systems. This technology offers confidence for regular athlete monitoring during activities like squats and landings.

Keywords:
deep learningmeasurement errorpose estimationrepeatability

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Area of Science:

  • Biomechanics
  • Motion Capture Technology
  • Sports Science

Background:

  • Markerless motion capture offers potential for repeated biomechanical data collection during injury-related activities.
  • Limited research has evaluated the reliability of markerless motion capture for single-leg tasks.

Purpose of the Study:

  • To assess the between-day reliability of trunk and lower limb kinematics during single-leg squat and landing tasks using markerless motion capture.
  • To compare the between-day reliability of markerless motion capture with marker-based motion capture for the same tasks.

Main Methods:

  • Nineteen recreational athletes performed single-leg squat and landing tasks in two sessions one week apart.
  • Trunk, hip, knee, and ankle joint angles were analyzed using markerless (Theia3D) and marker-based motion capture.
  • Reliability was assessed using full-curve analysis (RMSD, SPM) and discrete point analysis (ICC, SEM).

Main Results:

  • Markerless motion capture showed low mean RMSD for all joints and planes during single-leg squat and landing tasks.
  • Discrete point analysis indicated moderate to good reliability (ICC: 0.77-0.83) with low SEM values for markerless motion capture.
  • Marker-based motion capture demonstrated slightly higher RMSD and SEM values but good relative reliability (ICC: 0.88-0.90).

Conclusions:

  • Markerless motion capture, specifically Theia3D, provides reliable kinematic data for single-leg tasks.
  • The measurement errors are comparable to marker-based systems, supporting its use for regular athlete monitoring.