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.

1AbstractDuring the last decade, pain scales including facial expressions as indicators of pain have been developed for horses, mostly relying on direct observations or inspection of images. Despite differences in the research conditions and methodology the different scales focus on the same regions of the face, corresponding to moveable facial muscles related to the ears, eyes, nostrils, lips and chin. However, a detailed comparison of the facial activities occurring during pain is not possible. We used a Facial Action Coding System modified for horses to code and analyse video recordings from an earlier study of acute short-term experimental pain and from clinical cases with and without pain. We demonstrated for the first time EquiFACS based changes to pain in video of horses, using traditional statistical methods based on frequency, and novel analyses based on sliding observation windows and co-occurrence of facial actions. The most prominent differences of the experimental horses were related to the lower face actions chin raiser and nostril dilator, while less prominent, but significantly more frequent actions were related to the eye region, inner brow raiser (AU101), increased eye white (AD1), half blink (AU47), and ear rotator (EAD104). Ears forward (EAD101) and eye blink (AU145) were not associated to pain. Based on this we selected the two lower face actions for analysis of the clinical videos, and found that their co-occurrence within a window of 10 to 15 second gave 100% positive predictive values, as compared to the rating from three expert pain raters. Using our developed co-occurrence analyses we were surprised to detect that the chance of identifying three or more of the facial actions related to pain in 0.04 second sequence, corresponding to one frame, was below 3%, indicating that use of randomly selected images for pain scoring may be a very insensitive method.