Equine Facial Action Coding System for determination of pain-related facial responses in videos of horses.
- Journal Article
- Research Support
- Non-U.S. Gov't
Summary
The research focuses on the development of a system for assessing pain in horses by analyzing their facial expressions. The Facial Action Coding System (FACS), modified for horses, was used to observe and analyze video footage of horses in varied pain situations, with a focus on facial muscles related to ears, eyes, nostrils, lips, and chin.
Methodology
- The researchers used a modified version of the Facial Action Coding System (FACS) designed for horses, known as EquiFACS.
- The study involved the analysis of video recordings involving instances of acute short-term experimental pain (in 6 cases) and selected clinical cases (21 cases), where horses were expected to either experience pain or not.
- The team used statistical methods to analyze the data. These methods included a frequency-based method borrowed from human FACS approaches and another innovative method based on the simultaneous occurrence of facial actions in varying time slots.
Finding
- The researchers observed changes in crucial indicators of pain through the videos, identifying specific behaviors in the ear rotator, nostril dilator, and lower face, notably chin raiser behaviors.
- The inner brow raiser and eye white increase behaviors showed less consistent results across experimental and clinical data collected.
- The frequency-based approach managed to pinpoint movements or actions and behaviors that corresponded well to earlier established indicators of pain in horses.
- Furthermore, the co-occurrence-based method highlighted more specific lower face behaviors that, while not frequent, were specific to pain expressions in horses and showed better consistency in results for both experimental and clinical data.
- Chewing was found to be unique to horses in pain, based on the co-occurrence-based method.
- Newly observed indicators of pain included an increased frequency of half blink in the horses studied.
Conclusion
The research highlights the potential of the EquiFACS in helping to objectively identify pain in horses by observing and decoding their facial expressions. This approach could have broader implications in the care and treatment of horses, enabling a more effective way to detect and manage pain in these animals. The new indicators of pain identified in the research can enhance existing techniques in veterinary diagnostics and treatments. They can also provide a basis for further research in the area of pain assessment in horses and other animals.
Cite This Article
Publication
Researcher Affiliations
- Dept. Computer Science, University of California Davis, Davis, California, United States of America.
- Dept. Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences, Uppsala, Sweden.
- Dept. Clinical Sciences, University of Copenhagen, Taastrup, Denmark.
- Dept. Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
MeSH Terms
- Animals
- Facial Expression
- Facial Muscles / physiopathology
- Facial Pain / diagnosis
- Facial Pain / veterinary
- Female
- Horse Diseases / diagnosis
- Horses
- Male
- Pain Measurement / methods
- Video Recording
Conflict of Interest Statement
References
- Hadjistavropoulos T, Craig KD. A theoretical framework for understanding self-report and observational measures of pain: a communications model.. Behaviour research and therapy 2002;40(5):551–570.
- Flecknell P, Leach M, Bateson M. Affective state and quality of life in mice.. Pain 2011;152(5):963–964.
- IASP Taxonomy: International Association for the Study of Pain; 2016;. http://www.iasp-pain.org/Education/Content.aspx?ItemNumber=1698.
- Raekallio M, Taylor PM, Bloomfield M. A comparison of methods for evaluation of pain and distress after orthopaedic surgery in horses.. Journal of Veterinary Anaesthesia 1997;24(2):17–20.
- Price J, Catriona S, Welsh EM, Waran NK. Preliminary evaluation of a behaviour–based system for assessment of post–operative pain in horses following arthroscopic surgery.. Veterinary anaesthesia and analgesia 2003;30(3):124–137.
- Sellon DC, Roberts MC, Blikslager AT, Ulibarri C, Papich MG. Effects of continuous rate intravenous infusion of butorphanol on physiologic and outcome variables in horses after celiotomy.. Journal of Veterinary Internal Medicine 2004;18(4):555–563.
- Graubner C, Gerber V, Doherr M, Spadavecchia C. Clinical application and reliability of a post abdominal surgery pain assessment scale (PASPAS) in horses.. The Veterinary Journal 2011;188(2):178–183.
- van Loon JP, Van Dierendonck MC. Monitoring acute equine visceral pain with the Equine Utrecht University Scale for Composite Pain Assessment (EQUUS-COMPASS) and the Equine Utrecht University Scale for Facial Assessment of Pain (EQUUS-FAP): A scale-construction study.. The Veterinary Journal 2015;206(3):356–364.
- Gleerup K, Lindegaard C. Recognition and quantification of pain in horses: A tutorial review.. Equine Veterinary Education 2016;28(1):47–57.
- Dalla Costa E, Minero M, Lebelt D, Stucke D, Canali E, Leach MC. Development of the Horse Grimace Scale (HGS) as a pain assessment tool in horses undergoing routine castration.. PLoS one 2014;9(3):e92281.
- Gleerup KB, Forkman B, Lindegaard C, Andersen PH. An equine pain face.. Veterinary anesthesia and analgesia 2015;42(1):103–114.
- Dalla Costa E, Pascuzzo R, Leach MC, Dai F, Lebelt D, Vantini S. Can grimace scales estimate the pain status in horses and mice? A statistical approach to identify a classifier.. PloS one 2018;13(8):e0200339.
- Ekman P, Friesen WV, Hager JC. Facial Action Coding System. Manual and Investigator’s Guide.. 2002.
- Wathan J, Burrows AM, Waller BM, McComb K. EquiFACS: The Equine Facial Action Coding System.. PloS one 2015;10(8):e0131738.
- Sayette MA, Cohn JF, Wertz JM, Perrott MA, Parrott DJ. A psychometric evaluation of the facial action coding system for assessing spontaneous expression.. Journal of Nonverbal Behavior 2001;25(3):167–185.
- Kunz M, Meixner D, Lautenbacher S. Facial muscle movements encoding pain—a systematic review.. Pain 2019;160(3):535–549.
- Hampton AJ, Hadjistavropoulos T, Gagnon MM, Williams J, Clark D. The effects of emotion regulation strategies on the pain experience: a structured laboratory investigation.. Pain 2015;156(5):868–879.
- Prkachin KM. The consistency of facial expressions of pain: a comparison across modalities.. Pain 1992;51(3):297–306.
- Karmann AJ, Maihöfner C, Lautenbacher S, Sperling W, Kornhuber J, Kunz M. The role of prefrontal inhibition in regulating facial expressions of pain: a repetitive transcranial magnetic stimulation study.. The Journal of Pain 2016;17(3):383–391.
- Krumhuber EG, Kappas A, Manstead AS. Effects of dynamic aspects of facial expressions: A review.. Emotion Review 2013;5(1):41–46.
- Lindegaard C, Thomsen MH, Larsen S, Andersen PH. Analgesic efficacy of intra-articular morphine in experimentally induced radiocarpal synovitis in horses.. Veterinary anaesthesia and analgesia 2010;37(2):171–185.
- ELAN. Max Planck Institute for Psycholinguistics, The Language Archive, Nijmegen, The Netherlands;.
- Bron C, Kerbosch J. Algorithm 457: finding all cliques of an undirected graph.. Communications of the ACM 1973;16(9):575–577.
- Merkies K, Ready C, Farkas L, Hodder A. Eye Blink Rates and Eyelid Twitches as a Non-Invasive Measure of Stress in the Domestic Horse.. Animals 2019;9(8):562.
- Hintze S, Smith S, Patt A, Bachmann I, Würbel H. Are eyes a mirror of the soul? What eye wrinkles reveal about a horse’s emotional state.. PloS one 2016;11(10):e0164017.
- Gleerup KB, Andersen PH, Munksgaard L, Forkman B. Pain evaluation in dairy cattle.. Applied Animal Behaviour Science 2015;171:25–32.
- Wathan J, McComb K. The eyes and ears are visual indicators of attention in domestic horses.. Current Biology 2014;24(15):R677–R679.
Citations
This article has been cited 16 times.- Correia-Caeiro C, Zamansky A, Karl S, Bremhorst A. Research Methods for the Analysis of Visual Emotion Cues in Animals: A Workshop Report. Animals (Basel) 2025 Oct 29;15(21).
- da Fé VCS, Dos Santos VMO, de Lima ACB, Hernandes MSP, Caldara FR, Gomes MNB. Auditory enrichment on facial and physiological responses of Pantaneiro geldings and mares under short-term stress. PLoS One 2025;20(5):e0323649.
- Mota-Rojas D, Whittaker AL, Bienboire-Frosini C, Buenhombre J, Mora-Medina P, Domínguez-Oliva A, Martínez-Burnes J, Hernández-Avalos I, Olmos-Hernández A, Verduzco-Mendoza A, Casas-Alvarado A, Lezama-García K, Grandin T. The neurobiological basis of emotions and their connection to facial expressions in non-human mammals: insights in nonverbal communication. Front Vet Sci 2025;12:1541615.
- Lundblad J, Rhodin M, Hernlund E, Bjarnestig H, Hidén Rudander S, Haubro Andersen P. Facial expressions during compound interventions of nociception, conspecific isolation, and sedation in horses. Sci Rep 2025 Feb 13;15(1):5373.
- Chiavaccini L, Gupta A, Anclade N, Chiavaccini G, De Gennaro C, Johnson AN, Portela DA, Romano M, Vettorato E, Luethy D. Automated acute pain prediction in domestic goats using deep learning-based models on video-recordings. Sci Rep 2024 Nov 7;14(1):27104.
- Chiavaccini L, Gupta A, Chiavaccini G. From facial expressions to algorithms: a narrative review of animal pain recognition technologies. Front Vet Sci 2024;11:1436795.
- Ask K, Rhodin M, Rashid-Engström M, Hernlund E, Andersen PH. Changes in the equine facial repertoire during different orthopedic pain intensities. Sci Rep 2024 Jan 2;14(1):129.
- Tomberg C, Petagna M, de Selliers de Moranville LA. Horses (Equus caballus) facial micro-expressions: insight into discreet social information. Sci Rep 2023 May 27;13(1):8625.
- Boneh-Shitrit T, Feighelstein M, Bremhorst A, Amir S, Distelfeld T, Dassa Y, Yaroshetsky S, Riemer S, Shimshoni I, Mills DS, Zamansky A. Explainable automated recognition of emotional states from canine facial expressions: the case of positive anticipation and frustration. Sci Rep 2022 Dec 30;12(1):22611.
- McVey C, Egger D, Pinedo P. Improving the Reliability of Scale-Free Image Morphometrics in Applications with Minimally Restrained Livestock Using Projective Geometry and Unsupervised Machine Learning. Sensors (Basel) 2022 Oct 31;22(21).
- Carvalho JRG, Trindade PHE, Conde G, Antonioli ML, Funnicelli MIG, Dias PP, Canola PA, Chinelatto MA, Ferraz GC. Facial Expressions of Horses Using Weighted Multivariate Statistics for Assessment of Subtle Local Pain Induced by Polylactide-Based Polymers Implanted Subcutaneously. Animals (Basel) 2022 Sep 13;12(18).
- Feighelstein M, Shimshoni I, Finka LR, Luna SPL, Mills DS, Zamansky A. Automated recognition of pain in cats. Sci Rep 2022 Jun 10;12(1):9575.
- Broomé S, Ask K, Rashid-Engström M, Haubro Andersen P, Kjellström H. Sharing pain: Using pain domain transfer for video recognition of low grade orthopedic pain in horses. PLoS One 2022;17(3):e0263854.
- Lencioni GC, de Sousa RV, de Souza Sardinha EJ, Corrêa RR, Zanella AJ. Pain assessment in horses using automatic facial expression recognition through deep learning-based modeling. PLoS One 2021;16(10):e0258672.
- Andersen PH, Broomé S, Rashid M, Lundblad J, Ask K, Li Z, Hernlund E, Rhodin M, Kjellström H. Towards Machine Recognition of Facial Expressions of Pain in Horses. Animals (Basel) 2021 Jun 1;11(6).
- Lundblad J, Rashid M, Rhodin M, Haubro Andersen P. Effect of transportation and social isolation on facial expressions of healthy horses. PLoS One 2021;16(6):e0241532.