ArticlePloS one2024
Automated recognition of emotional states of horses from facial expressions.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Hyperflexing the horse's neck: a systematic review and meta-analysis.Scientific reports · 2024Pooled it
- Artificial intelligence-based automated scoring of the mouse grimace scale: a systematic review.Pain reports · 2026Review
- Longitudinal welfare assessment in French jump racehorses during season preparation.Equine veterinary journal · 2026Article
- Technologies for equine welfare and performance monitoring under field conditions - Where do we stand?Equine veterinary journal · 2026Review
- Smartphone-Based Technologies in Equine Sports Medicine: Supporting Athlete Management-A Review.Sensors (Basel, Switzerland) · 2026Review
- Multi-Modal Feature Fusion and Hierarchical Classification for Automated Equine-Human Interaction Behavior Recognition.Sensors (Basel, Switzerland) · 2026Article
- Research on improved models for facial expression recognition in mice with abnormal glucose metabolism.Scientific reports · 2026Article
- Identifying Novel Emotions and Wellbeing of Horses from Videos Through Unsupervised Learning.Sensors (Basel, Switzerland) · 2025Article
- No More Evasion: Redefining Conflict Behaviour in Human-Horse Interactions.Animals : an open access journal from MDPI · 2025Article
- Faces of time: a historical overview of rapid innovations in coding animal facial signals.Frontiers in veterinary science · 2025Review
- Correction: Automated recognition of emotional states of horses from facial expressions.PloS one · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Animal affective computing is an emerging new field, which has so far mainly focused on pain, while other emotional states remain uncharted territories, especially in horses. This study is the first to develop AI models to automatically recognize horse emotional states from facial expressions using data collected in a controlled experiment. We explore two types of pipelines: a deep learning one which takes as input video footage, and a machine learning one which takes as input EquiFACS annotations. The former outperforms the latter, with 76% accuracy in separating between four emotional states: baseline, positive anticipation, disappointment and frustration. Anticipation and frustration were difficult to separate, with only 61% accuracy.
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Registered trials
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.