Horses have the ability to generate a remarkable repertoire of facial expressions, some of which have been linked to the affective component of pain. This study describes the facial expressions in healthy horses free of pain before and during transportation and social isolation, which are putatively stressful but ordinary management procedures. Transportation was performed in 28 horses by subjecting them to short-term road transport in a horse trailer. A subgroup (n = 10) of these horses was also subjected to short-term social isolation. During all procedures, a body-mounted, remote-controlled heart rate monitor provided continuous heart rate measurements. The horses’ heads were video-recorded during the interventions. An exhaustive dataset was generated from the selected video clips of all possible facial action units and action descriptors, time of emergency, duration, and frequency according to the Equine Facial Action Coding System (EquiFACS). Heart rate increased during both interventions (p<0.01), confirming that they caused disruption in sympato-vagal balance. Using the current method for ascribing certain action units (AUs) to specific emotional states in humans and a novel data-driven co-occurrence method, the following facial traits were observed during both interventions: eye white increase (p<0.001), nostril dilator (p<0.001), upper eyelid raiser (p<0.001), inner brow raiser (p = 0.042), tongue show (p<0.001). Increases in ‘ear flicker’ (p<0.001) and blink frequency (p<0.001) were also seen. These facial actions were used to train a machine-learning classifier to discriminate between the high-arousal interventions and calm horses, which achieved at most 79% accuracy. Most facial features identified correspond well with previous findings on behaviors of stressed horses, for example flared nostrils, repetitive mouth behaviors, increased eye white, tongue show, and ear movements. Several features identified in this study of pain-free horses, such as dilated nostrils, eye white increase, and inner brow raiser, are used as indicators of pain in some face-based pain assessment tools. In order to increase performance parameters in pain assessment tools, the relations between facial expressions of stress and pain should be studied further.
Automated recognition of human facial expressions of pain and emotions is to a certain degree a solved problem, using approaches based on computer vision and machine learning. However, the application of such methods to horses has proven difficult. Major barriers are the lack of sufficiently large, annotated databases for horses and difficulties in obtaining correct classifications of pain because horses are non-verbal. This review describes our work to overcome these barriers, using two different approaches. One involves the use of a manual, but relatively objective, classification system for facial activity (Facial Action Coding System), where data are analyzed for pain expressions after coding using machine learning principles. We have devised tools that can aid manual labeling by identifying the faces and facial keypoints of horses. This approach provides promising results in the automated recognition of facial action units from images. The second approach, recurrent neural network end-to-end learning, requires less extraction of features and representations from the video but instead depends on large volumes of video data with ground truth. Our preliminary results suggest clearly that dynamics are important for pain recognition and show that combinations of recurrent neural networks can classify experimental pain in a small number of horses better than human raters.
Many horses, just before and during their athletic career, show vertical movement asymmetries, to the same degree as clinically lame horses. It is unknown whether these asymmetries are caused by pain or have alternative explanations, such as inherent biological variation. In the latter case, movement asymmetries would be expected to be present at a very young age. This study aimed to investigate the prevalence of movement asymmetries in foals. Motion analysis, using an inertial measurement unit-based system (Equinosis), was performed on 54 foals (31 Swedish Warmbloods, 23 Standardbreds) during straight-line trot. The foals were between 4–13 weeks old and considered sound by their owners. Differences between the vertical minimum and maximum values recorded for the head (HDmin, HDmax) and pelvis (PDmin, PDmax) between left and right stance were calculated for each stride and an average was computed for each trial. Thresholds for asymmetry were defined as absolute trial mean >6 mm for HDmin and HDmax, and >3 mm for PDmin and PDmax. These thresholds were exceeded for one or several parameters by 83% of Standardbred foals and 45% of Swedish Warmblood foals, demonstrating surprisingly high prevalence of asymmetries in young foals, although the risk of repetitive strain injuries and cumulative risk of trauma injuries was expected to be low in this age group. Standardbred foals showed similar prevalence of asymmetries to that reported previously for yearling Standardbred trotters, so relatively higher prevalence of movement asymmetries may be expected among trotters as a breed. In general, vertical head and pelvic movement asymmetries can be anticipated among foals considered sound by their owners. A better understanding of the aetiology of asymmetries is needed for correct interpretation of objective symmetry measurements in different populations of horses.
Horses have the ability to generate a remarkable repertoire of facial expressions, some which have been linked to certain emotional states, for example pain. Studies suggest that facial expressions may be a more ‘honest’ expression of emotional state in horses than behavioral or physiological parameters. This study sought to describe the facial expressions during stress of healthy horses free of pain, using a standardized method of recording facial expressions in video. Stress was induced in 28 horses by subjecting them to road transport and 10 of these horses were also subjected to social isolation. The horses served as their own control. A body-mounted, remote controlled heart rate monitor provided continuous heart rate measurements during the interventions. The horses’ facial expressions were video-recorded during the interventions. Frequency and duration of each facial expression were then determined, according to the Equine Facial Action Coding System. Heart rate increased during the stressful interventions (p=0.01), confirming that the interventions were stressful. Using both the human investigation- and the co-occurrence methods, the following facial traits could be observed during stress: eye white increase (p<0.001), nostril dilator (p<0.001), upper eyelid raiser (p<0.001), inner brow raiser (p=0.042), tongue show (p<0.001) along with an increase in ‘ear flicker’ (p<0.001) and blink frequency (p<0.001). The facial actions were successfully used to train a machine-learning classifier to discriminate between stressed and calm horses, with an accuracy of 74.2 %. Most of the facial features identified correspond well with previous research on the subject, for example flared nostrils, repetitive mouth behaviors, increased eye white, tongue show and ear movements. Some features selected as indicative of emotional pain-free stress are used in face-based pain assessment tools, such as dilated nostrils, eye white increase or inner brow raiser. The relation between facial expressions of stress and pain should therefore further be studied.
Background: Nerve growth factor (NGF) is a neurotrophin that is increased in osteoarthritic joints of horses. In humans, NGF has been associated with pain, and both synovial and serum NGF concentrations are increased in osteoarthritic patients. Studies in humans also have shown that serum NGF concentration can increase with stress. Serum NGF concentration should be evaluated in horses with osteoarthritis-associated lameness.Objectives: Quantify and compare serum NGF concentration in horses with osteoarthritis-associated lameness and sound horses. Additionally, the impact of short-term stress on serum NGF concentration was investigated.Animals: Lame horses with radiographic evidence of osteoarthritis (n = 20), lame horses without radiographic changes in the affected joint (n = 20) and sound horses (n = 20). In addition, horses with acute fractures (n = 9) were sampled. To determine the effect of stress, serum from horses subjected to a stressful event (transportation, n = 5; stress confirmed by increased serum cortisol concentration) was analyzed.Methods: Cross-sectional clinical study (lame, sound, and fracture cohorts) and experimental longitudinal study (stress cohort). Serum NGF concentration was determined using a quantitative sandwich ELISA.Results: Serum NGF concentration was increased in lame horses with radiographic evidence of osteoarthritis (P < .0001; median, 238 pg/mL; interquartile range [IQR], 63-945 pg/mL) and in lame horses without radiographic evidence of osteoarthritis in the painful joint (P < .05; median, 31 pg/mL; IQR, 31-95 pg/mL) compared with sound horses (median, 31 pg/mL; IQR, 31-46 pg/mL). Serum NGF concentration did not increase with short-term stress and was low in horses with fractureassociated pain.Conclusions and Clinical Importance: Serum NGF concentration was high in the cohort with advanced osteoarthritis and should be investigated as a marker for osteoarthritis-associated pain.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.