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Equine veterinary journal2025; doi: 10.1111/evj.14516

Agreement between subjective gait assessment and markerless video gait-analysis in endurance horses.

Abstract: 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. Objective: 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. Methods: 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). Conclusions: 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.
© 2025 The Author(s). Equine Veterinary Journal published by John Wiley & Sons Ltd on behalf of EVJ Ltd.
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Publication Date: 2025-04-21 PubMed ID: 40257418DOI: 10.1111/evj.14516Google Scholar: Lookup
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Summary

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This research examines the agreement between the subjective evaluation of a horse’s gait, conducted by official endurance veterinarians (OEVs), and an objective analysis of the horse’s gait using a markerless artificial intelligence motion tracking system (AI-MTS). The study found that the AI-MTS system could potentially be useful in assisting veterinarians during endurance competitions.

Objective of the Research

  • The objective of this research was to investigate the level of agreement between two methods used to evaluate the gait of endurance horses – a subjective assessment by an official endurance veterinarian and an objective evaluation using a markerless artificial intelligence motion tracking system (AI-MTS).

Methodology of the Research

  • The study used a cross-sectional design involving 110 horses from three different endurance competitions.
  • The official endurance veterinarian conducted a total of 188 gait examinations using their subjective evaluation.
  • At the same time, each evaluation was recorded using a smartphone, and the data was later analyzed using the AI-MTS system.
  • The gaits were classified into three levels: no asymmetry, mild asymmetry, and severe asymmetry.
  • The agreement between the two methods was measured using Fleiss’ multi-rater kappa statistic (ĸ).

Results of the Research

  • The research found that the overall agreement between the subjective evaluation by a veterinarian and gait analysis using the AI-MTS system was fair, with a kappa statistic value of 0.26.
  • For the three gait asymmetry categories, the highest level of agreement was found in the ‘severe’ category, with a kappa statistic value of 0.75.
  • The ‘no asymmetry’ category had a fair agreement, with a kappa statistic of 0.25.
  • The agreement for the ‘mild’ category was the lowest and not significant, with a kappa statistic of 0.13.

Conclusions from the Research

  • The results showed that the ‘mild’ category was the most challenging to identify through both methods.
  • There was substantial agreement between the two methods for the ‘severe’ category of gait asymmetry.
  • The research concluded that the AI-MTS can be a helpful tool in making decision-making during endurance competitions by providing a more objective evaluation of a horse’s gait.

Cite This Article

APA
de Chiara M, Montano C, De Matteis A, Guidi L, Buono F, Auletta L, Del Prete C, Pasolini MP. (2025). Agreement between subjective gait assessment and markerless video gait-analysis in endurance horses. Equine Vet J. https://doi.org/10.1111/evj.14516

Publication

Equine veterinary journal
ISSN: 2042-3306
NlmUniqueID: 0173320
Country: United States
Language: English

Researcher Affiliations

de Chiara, Mariaelena
  • Department of Veterinary Medicine and Animal Production, University of Naples Federico II, Naples, Italy.
Montano, Chiara
  • Department of Veterinary Medicine and Animal Production, University of Naples Federico II, Naples, Italy.
De Matteis, Andrea
  • Department of Veterinary Medicine and Animal Production, University of Naples Federico II, Naples, Italy.
Guidi, Livia
  • Freelance Veterinary Practitioner, Avellino, Italy.
Buono, Francesco
  • Department of Veterinary Medicine and Animal Production, University of Naples Federico II, Naples, Italy.
Auletta, Luigi
  • Department of Veterinary Medicine and Animal Science (DIVAS), University of Milan, Lodi, Italy.
Del Prete, Chiara
  • Department of Veterinary Medicine and Animal Production, University of Naples Federico II, Naples, Italy.
Pasolini, Maria Pia
  • Department of Veterinary Medicine and Animal Production, University of Naples Federico II, Naples, Italy.

Grant Funding

  • University of Naples Federico II

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Citations

This article has been cited 1 times.
  1. Gottleib K, Trager-Burns L, Santonastaso A, Bogers S, Werre S, Burns T, Byron C. Comparison of Gait Characteristics for Horses Without Shoes, with Steel Shoes, and with Aluminum Shoes. Animals (Basel) 2025 Aug 13;15(16).
    doi: 10.3390/ani15162376pubmed: 40867705google scholar: lookup
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