Related Experiment Video
Updated: May 10, 2025
Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder
Published on: March 4, 2018
Agreement between subjective gait assessment and markerless video gait-analysis in endurance horses
Mariaelena de Chiara1, Chiara Montano1, Andrea De Matteis1
1Department of Veterinary Medicine and Animal Production, University of Naples Federico II, Naples, Italy.
Background:
Subjective evaluation of gait by official endurance veterinarians (OEVs) is used to determine 'fitness-to-compete' in horses participating in endurance competitions. Objective gait analysis systems could aid in quick and verifiable judgements.
Objectives:
To assess the agreement between objective analysis of head and pelvis vertical movement asymmetry performed with a markerless artificial intelligence motion tracking system (AI-MTS) and subjective lameness assessment performed by an accredited FEI OEV to judge horse gaits.
Study Design:
Cross-sectional.
Methods:
During three endurance competitions, 110 horses were enrolled. The OEV performed 188 gait examinations, which were simultaneously recorded with a smartphone. The vertical motion asymmetry of the head and pelvis was later analysed from the videos through the AI-MTS application. The gaits were scored as 'no asymmetry', 'mild asymmetry' or 'severe asymmetry'. The agreement was evaluated using Fleiss' multi-rater kappa statistic (κ).
Results:
The overall agreement between the two methods was fair (k = 0.26, p < 0.001). Within the three gait asymmetry categories, substantial agreement was obtained for the 'severe' (k = 0.75, p < 0.001) category, fair agreement was detected for the 'no asymmetry' category (k = 0.25, p < 0.001), and no agreement was identified for the 'mild' category (k = 0.13, p = 0.08).
Main Limitations:
Comparison between AI-MTS and a single OEV; absence of a tripod during video recording; and video recording from a different point of view than the OEVs.
Conclusions:
Mild asymmetry was the most challenging gait category to identify. Substantial agreement between the subjective lameness evaluation by OEV and AI-MTS assessment was observed for the 'severe' category. AI-MTS may be a helpful tool to assist OEVs in decision-making during endurance competitions.
