ArticleEquine veterinary journal2025
Objective movement asymmetry in horses is comparable between markerless technology and sensor-based systems.
Article in Equine veterinary journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 15 citations in OpenAlex.
- Reliability, agreement and variability of a markerless computer vision algorithm for equine gait analysis under field conditions.Equine veterinary journal · 2026Article
- Validation of a handheld smartphone markerless gait-analysis tool using an estimated groundline in horses.Equine veterinary journal · 2026Article
- Agreement between veterinarians and three objective evaluation systems in naturally occurring equine lameness.Equine veterinary journal · 2026Article
- Smartphone-Based Technologies in Equine Sports Medicine: Supporting Athlete Management-A Review.Sensors (Basel, Switzerland) · 2026Review
- The influence, promise, and potential perils of artificial intelligence in veterinary medicine: a call for improved awareness and literacy.Journal of veterinary internal medicine · 2026Article
- Agreement between subjective gait assessment and markerless video gait-analysis in endurance horses.Equine veterinary journal · 2026Article
- Evaluating the Accuracy of a Vision-Based Algorithm for Groundline Estimation in Trotting Horses Using Multiple Camera Angles.Veterinary medicine and science · 2026Article
- A Markerless Approach for Full-Body Biomechanics of Horses.Animals : an open access journal from MDPI · 2025Article
- Evaluation of water treadmill training, lunging and treadmill training in the rehabilitation of horses with back pain.BMC veterinary research · 2025Article
- Objective Evaluation of Gait Asymmetries in Traditional Racehorses During Pre-Race Inspection: Application of a Markerless AI System in Straight-Line and Lungeing Conditions.Animals : an open access journal from MDPI · 2025Article
- Vertical Movement of Head, Withers, and Pelvis of High-Level Dressage Horses Trotting in Hand vs. Being Ridden.Animals : an open access journal from MDPI · 2025Article
- Objective movement asymmetry in horses is comparable between markerless technology and sensor-based systems.Equine veterinary journal · 2025Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
backgroundA markerless artificial intelligence (AI) system for lameness detection has recently become available but has not been extensively compared with commonly used inertial measurement unit (IMU) systems for detecting asymmetry under field conditions.
objectiveComparison of classification of asymmetric limbs under field conditions and comparison of normalised asymmetry data using a markerless AI system (SleipAI; recorded on a tripod mounted iPhone 14pro [SL]); the Equinosis Q Lameness Locator (LL); the EquiMoves (EM); and subjective evaluation (SE). STUDY
designDescriptive clinical study.
methodsStraight line trot data were collected from 52 client-owned horses in regular training. Limbs were categorised as symmetric or asymmetric. Number of analysed strides were compared with Wilcoxon's each pairs test. Inter-rater reliability in classification of asymmetric limbs was assessed with Light's Kappa. Bland Altman analysis of normalised asymmetry data was performed.
resultsData from 41 horses were included. Most horses showed mild asymmetry. The EM analysed significantly more strides than the other systems, both for forelimbs and for hindlimbs (53 ± 11 strides for both, respectively; p < 0.006). The LL analysed significantly more hindlimbs strides (45 ± 13) than the SL (27 ± 6; p < 0.001). Moderate inter-rater agreement for asymmetry classification was found between systems (k = 0.59 forelimbs; 0.44 hindlimbs); agreement decreased when including the SE. For the normalised asymmetry data, the strongest agreement was found between the two IMU systems. MAIN LIMITATIONS: Horses were assessed during straight-line trot only.
conclusionsThe objective systems were comparable in classification of asymmetric limbs under field conditions when using defined asymmetry thresholds. Discrepancies stemmed largely from the imposed thresholds (i.e., systems largely identified same-side asymmetry). Overall, the strongest agreement was found between LL and EM. The SL analysed significantly fewer hindlimb strides than the LL and EM which could represent a limitation of the Sleip AI.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.