Equine and Animal Cognition Reference Database -- Query Results

Dyson, S., Berger, J., Ellis, A. D., & Mullard, J. (2018). Development of an ethogram for a pain scoring system in ridden horses and its application to determine the presence of musculoskeletal pain. Journal of Veterinary Behavior, 23, 47–57. Abstract: There is evidence that more than 47% of the sports horse population in normal work may be lame, but the lameness is not recognized by owners or trainers. An alternative means of detecting pain may be recognition of behavioral changes in ridden horses. It has been demonstrated that there are differences in facial expressions in nonlame and lame horses. The purpose of this study was to develop a whole horse ethogram for ridden horses and to determine whether it could be applied repeatedly by 1 observer (repeatability study, 9 horses) and if, by application of a related pain behavior score, lame horses (n = 24) and nonlame horses (n = 13) could be differentiated. It was hypothesized that there would be some overlap in pain behavior scores among nonlame and lame horses; and that overall, nonlame horses would have a lower pain behavior score than lame horses. The ethogram was developed with 117 behavioral markers, and the horses were graded twice in random order by a trained specialist using video footage. Overall, there was a good correlation between the 2 assessments (P < 0.001; R2 = 0.91). Behavioral markers that were not consistent across the 2 assessments were omitted, reducing the ethogram to 70 markers. The modified ethogram was applied to video recordings of the nonlame horses and lame horses (ethogram evaluation). There was a strong correlation between 20 behavioral markers and the presence of lameness. The ethogram was subsequently simplified to 24 behavioral markers, by the amalgamation of similar behaviors which scored similarly and by omission of markers which showed unreliable results in relation to lameness. Following this, the maximum individual occurrence score for lame horses was 14 (out of 24 possible markers), with a median and mean score of 9 (±2 standard deviation) compared with a maximum score of 6 for nonlame horses, with a median and mean score of 2 (±1.4). For lame horses, the following behaviors occurred significantly more (P < 0.05, chi-square): ears back, mouth opening, tongue out, change in eye posture and expression, going above the bit, head tossing, tilting the head, unwillingness to go, crookedness, hurrying, changing gait spontaneously, poor quality canter, resisting, and stumbling and toe dragging. Recognition of these features as potential indicators of musculoskeletal pain may enable earlier recognition of lameness and avoidance of punishment-based training. Further research is necessary to verify this new ethogram for assessment of pain in ridden horses. Keywords: Lameness; Equine behavior; Pain grading; Headshaking; Bucking; Rearing https://references.equine-behaviour.de/show.php?record=6706
Scheibe, K. M., & Gromann, C. (2006). Application testing of a new three-dimensional acceleration measuring system with wireless data transfer (WAS) for behavior analysis (Vol. 38). Abstract: A wireless acceleration measurement system was applied to free-moving cows and horses. Sensors were available as a collar and a flat box for measuring leg or trunk movements. Results were transmitted simultaneously by radio or stored in an 8-MB internal memory. As analytical procedures, frequency distributions with standard deviations, spectral analyses, and fractal analyses were applied. Bymeans of the collar sensor, basic behavior patterns (standing, grazing, walking, ruminating, drinking, and hay uptake) could be identified in cows. Lameness could be detected in cows and horses by means of the leg sensor. The portion of basic and harmonic spectral components was reduced; the fractal dimension was reduced. The system can be used for the detection and analysis of even small movements of free-moving humans or animals over several hours. It is convenient for the analysis of basic behaviors, emotional reactions, or events causing flight or fright or for comparing different housing elements, such as floors or fences. Keywords: Acceleration; Animals; Behavior, Animal; Cattle; Cattle Diseases/diagnosis; Computer Communication Networks/instrumentation; Forelimb/physiopathology; Fractals; Hindlimb/physiopathology; Horse Diseases/diagnosis; Horses; Imaging, Three-Dimensional/instrumentation/methods/veterinary; Lameness, Animal/diagnosis; Monitoring, Ambulatory/instrumentation/methods; Motor Activity; Movement; Pattern Recognition, Automated/methods https://references.equine-behaviour.de/show.php?record=1775

Abstract: There is evidence that more than 47% of the sports horse population in normal work may be lame, but the lameness is not recognized by owners or trainers. An alternative means of detecting pain may be recognition of behavioral changes in ridden horses. It has been demonstrated that there are differences in facial expressions in nonlame and lame horses. The purpose of this study was to develop a whole horse ethogram for ridden horses and to determine whether it could be applied repeatedly by 1 observer (repeatability study, 9 horses) and if, by application of a related pain behavior score, lame horses (n = 24) and nonlame horses (n = 13) could be differentiated. It was hypothesized that there would be some overlap in pain behavior scores among nonlame and lame horses; and that overall, nonlame horses would have a lower pain behavior score than lame horses. The ethogram was developed with 117 behavioral markers, and the horses were graded twice in random order by a trained specialist using video footage. Overall, there was a good correlation between the 2 assessments (P < 0.001; R2 = 0.91). Behavioral markers that were not consistent across the 2 assessments were omitted, reducing the ethogram to 70 markers. The modified ethogram was applied to video recordings of the nonlame horses and lame horses (ethogram evaluation). There was a strong correlation between 20 behavioral markers and the presence of lameness. The ethogram was subsequently simplified to 24 behavioral markers, by the amalgamation of similar behaviors which scored similarly and by omission of markers which showed unreliable results in relation to lameness. Following this, the maximum individual occurrence score for lame horses was 14 (out of 24 possible markers), with a median and mean score of 9 (±2 standard deviation) compared with a maximum score of 6 for nonlame horses, with a median and mean score of 2 (±1.4). For lame horses, the following behaviors occurred significantly more (P < 0.05, chi-square): ears back, mouth opening, tongue out, change in eye posture and expression, going above the bit, head tossing, tilting the head, unwillingness to go, crookedness, hurrying, changing gait spontaneously, poor quality canter, resisting, and stumbling and toe dragging. Recognition of these features as potential indicators of musculoskeletal pain may enable earlier recognition of lameness and avoidance of punishment-based training. Further research is necessary to verify this new ethogram for assessment of pain in ridden horses.

Keywords: Lameness; Equine behavior; Pain grading; Headshaking; Bucking; Rearing

https://references.equine-behaviour.de/show.php?record=6706

Abstract: A wireless acceleration measurement system was applied to free-moving cows and horses. Sensors were available as a collar and a flat box for measuring leg or trunk movements. Results were transmitted simultaneously by radio or stored in an 8-MB internal memory. As analytical procedures, frequency distributions with standard deviations, spectral analyses, and fractal analyses were applied. Bymeans of the collar sensor, basic behavior patterns (standing, grazing, walking, ruminating, drinking, and hay uptake) could be identified in cows. Lameness could be detected in cows and horses by means of the leg sensor. The portion of basic and harmonic spectral components was reduced; the fractal dimension was reduced. The system can be used for the detection and analysis of even small movements of free-moving humans or animals over several hours. It is convenient for the analysis of basic behaviors, emotional reactions, or events causing flight or fright or for comparing different housing elements, such as floors or fences.