ArticlePloS one2020
Equine Facial Action Coding System for determination of pain-related facial responses in videos of horses.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 38 citations in OpenAlex.
- Descriptive, comparative, and functional anatomy of the facial musculature in cattle (Bos taurus).Anatomical record (Hoboken, N.J. : 2007) · 2026Article
- Social enrichment mitigates facial expressions and physiological indicators of short-term stress in horses.PloS one · 2026Article
- Research Methods for the Analysis of Visual Emotion Cues in Animals: A Workshop Report.Animals : an open access journal from MDPI · 2025Article
- Facial expressions during compound interventions of nociception, conspecific isolation, and sedation in horses.Scientific reports · 2025Article
- Auditory enrichment on facial and physiological responses of Pantaneiro geldings and mares under short-term stress.PloS one · 2025Article
- The neurobiological basis of emotions and their connection to facial expressions in non-human mammals: insights in nonverbal communication.Frontiers in veterinary science · 2025Review
- Automated acute pain prediction in domestic goats using deep learning-based models on video-recordings.Scientific reports · 2024Article
- Changes in the equine facial repertoire during different orthopedic pain intensities.Scientific reports · 2024Article
- From facial expressions to algorithms: a narrative review of animal pain recognition technologies.Frontiers in veterinary science · 2024Review
- Horses (Equus caballus) facial micro-expressions: insight into discreet social information.Scientific reports · 2023Article
- Explainable automated recognition of emotional states from canine facial expressions: the case of positive anticipation and frustration.Scientific reports · 2022Article
- Improving the Reliability of Scale-Free Image Morphometrics in Applications with Minimally Restrained Livestock Using Projective Geometry and Unsupervised Machine Learning.Sensors (Basel, Switzerland) · 2022Article
- Facial Expressions of Horses Using Weighted Multivariate Statistics for Assessment of Subtle Local Pain Induced by Polylactide-Based Polymers Implanted Subcutaneously.Animals : an open access journal from MDPI · 2022Article
- Automated recognition of pain in cats.Scientific reports · 2022Article
- Sharing pain: Using pain domain transfer for video recognition of low grade orthopedic pain in horses.PloS one · 2022Article
- Towards Machine Recognition of Facial Expressions of Pain in Horses.Animals : an open access journal from MDPI · 2021Review
- Pain assessment in horses using automatic facial expression recognition through deep learning-based modeling.PloS one · 2021Article
- Effect of transportation and social isolation on facial expressions of healthy horses.PloS one · 2021Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
During the last decade, a number of pain assessment tools based on facial expressions have been developed for horses. While all tools focus on moveable facial muscles related to the ears, eyes, nostrils, lips, and chin, results are difficult to compare due to differences in the research conditions, descriptions and methodologies. We used a Facial Action Coding System (FACS) modified for horses (EquiFACS) to code and analyse video recordings of acute short-term experimental pain (n = 6) and clinical cases expected to be in pain or without pain (n = 21). Statistical methods for analyses were a frequency based method adapted from human FACS approaches, and a novel method based on co-occurrence of facial actions in time slots of varying lengths. We describe for the first time changes in facial expressions using EquiFACS in video of horses with pain. The ear rotator (EAD104), nostril dilation (AD38) and lower face behaviours, particularly chin raiser (AU17), were found to be important pain indicators. The inner brow raiser (AU101) and eye white increase (AD1) had less consistent results across experimental and clinical data. Frequency statistics identified AUs, EADs and ADs that corresponded well to anatomical regions and facial expressions identified by previous horse pain research. The co-occurrence based method additionally identified lower face behaviors that were pain specific, but not frequent, and showed better generalization between experimental and clinical data. In particular, chewing (AD81) was found to be indicative of pain. Lastly, we identified increased frequency of half blink (AU47) as a new indicator of pain in the horses of this study.
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