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Marker based and markerless motion capture for equestrian rider kinematic analysis: A comparative study.

Heather Cameron-Whytock1, Hannah Divall2, Martin Lewis3

  • 1School of Veterinary Medicine, University of Central Lancashire, Preston PR1 2HE, UK; School of Animal Rural and Environmental Science, Nottingham Trent University, Brackenhurst Campus, Southwell NG25 0QF, UK.

Journal of Biomechanics
|May 4, 2025
PubMed
Summary

Markerless motion capture offers a viable alternative to marker-based systems for equestrian rider analysis, particularly for trunk and hip angles. However, accuracy varies by joint and gait, requiring careful interpretation for specific applications like biofeedback.

Keywords:
Deep LearningEquestrianKinematicsMarkerless Motion CaptureRider

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Area of Science:

  • Biomechanics
  • Sports Technology
  • Equine Science

Background:

  • Marker-based motion capture is the traditional standard for kinematic analysis in sports.
  • Markerless motion capture offers a potentially more accessible and less intrusive alternative.
  • Assessing the accuracy of markerless systems in equestrian contexts is crucial for their adoption.

Purpose of the Study:

  • To compare the accuracy of a markerless motion capture system against a marker-based system for equestrian riders.
  • To evaluate joint and segment angle measurements during walking and trotting gaits.
  • To determine the suitability of markerless technology for rider kinematic analysis and biofeedback.

Main Methods:

  • Ten healthy adult riders performed walking and trotting trials on horseback.
  • Kinematic data were collected simultaneously using a 12-camera marker-based system and an 8-camera 2D video-based markerless system.
  • Three-dimensional hip, knee, shoulder, and elbow joint angles, along with trunk and pelvis angles, were computed and compared using root mean square difference (RMSD) and statistical parametric mapping (SPM).

Main Results:

  • The sagittal trunk angle exhibited the lowest RMSD (2.0°), while elbow rotation showed the highest (19°).
  • Markerless systems showed increased hip flexion and elbow flexion during walking gait compared to marker-based systems (p < 0.001).
  • No significant differences were found in the transverse plane, but RMSD tended to be higher, suggesting caution in interpretation.

Conclusions:

  • Markerless motion capture technology shows potential as an alternative to marker-based systems for equestrian rider assessment.
  • Accuracy is dependent on the specific joint/segment and the acceptable error margin.
  • While suitable for rider biofeedback, markerless systems may have limitations for precise analysis of certain joint movements, especially with obscured limbs during walking.