| Title: |
Agreement between subjective gait assessment and markerless video gait-analysis in endurance horses |
| Authors: |
de Chiara M.; Montano C.; De Matteis A.; Guidi L.; Buono F.; Auletta L.; Del Prete C.; Pasolini M. P. |
| Contributors: |
de Chiara, M.; Montano, C.; De Matteis, A.; Guidi, L.; Buono, F.; Auletta, L.; Del Prete, C.; Pasolini, M. P. |
| Publication Year: |
2025 |
| Collection: |
IRIS Università degli Studi di Napoli Federico II |
| Subject Terms: |
endurance; equine lamene; gait asymmetry; horse; markerless video gait analysis |
| Description: |
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. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
info:eu-repo/semantics/altIdentifier/wos/WOS:001471485900001; numberofpages:8; journal:EQUINE VETERINARY JOURNAL; https://hdl.handle.net/11588/1003620 |
| DOI: |
10.1111/evj.14516 |
| Availability: |
https://hdl.handle.net/11588/1003620; https://doi.org/10.1111/evj.14516 |
| Rights: |
info:eu-repo/semantics/openAccess ; license:Dominio pubblico ; license uri:http://creativecommons.org/publicdomain/zero/1.0/ |
| Accession Number: |
edsbas.86A57E61 |
| Database: |
BASE |