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PloS one2020; 15(11); e0231608; doi: 10.1371/journal.pone.0231608

Equine Facial Action Coding System for determination of pain-related facial responses in videos of horses.

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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Publication Date: 2020-11-03 PubMed ID: 33141852PubMed Central: PMC7608869DOI: 10.1371/journal.pone.0231608Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

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

APA
Rashid M, Silventoinen A, Gleerup KB, Andersen PH. (2020). Equine Facial Action Coding System for determination of pain-related facial responses in videos of horses. PLoS One, 15(11), e0231608. https://doi.org/10.1371/journal.pone.0231608

Publication

PloS one
ISSN: 1932-6203
NlmUniqueID: 101285081
Country: United States
Language: English
Volume: 15
Issue: 11
Pages: e0231608

Researcher Affiliations

Rashid, Maheen
  • Dept. Computer Science, University of California Davis, Davis, California, United States of America.
Silventoinen, Alina
  • Dept. Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Gleerup, Karina Bech
  • Dept. Clinical Sciences, University of Copenhagen, Taastrup, Denmark.
Andersen, Pia Haubro
  • 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

No competing interests.

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