Search Results (5)

Equine-Assisted Services (EAS) offer significant benefits for individuals with intellectual and/or physical disabilities. However, ensuring the welfare of the horses involved remains a key ethical concern. The objective of this study was to assess the affective states of horses involved in EAS while also establishing behavioural thresholds for indicators of positive or negative affective states. A total of 98 horses were observed over a two-month period, accumulating data about horse behaviour and session characteristics from 830 EAS sessions. Horses participating in coaching programs averaged four sessions in two months; those involved in therapeutic riding averaged 31 sessions. Equine behaviour and field experts defined behavioural thresholds to assess welfare standards. Negative state behaviours were predominantly aligned within excellent or neutral thresholds, while positive state behaviours were observed from unacceptable to excellent. Principal Component Analysis (PCA) of the gathered behavioural data identified six affective states in coaching sessions and four in therapeutic riding, explaining 63% and 73% of the total variation, respectively. Among these states, “comfortable” was the most frequently observed. Multiple linear regression showed several significant variables, highlighting the importance of health, suitable horse selection, and proper management in promoting positive affective states in EAS. Full article

Background: Autism spectrum disorder (ASD) is an early childhood and lifelong neurodevelopmental disorder. Many studies have confirmed that motor skills and physical activity interventions can improve motor development in ASD individuals and ultimately improve their quality of life. However, systematic evidence is lacking on whether motor skills and physical activity interventions improve motor development among children with ASD. Methods: A systematic search of the CNKI, PsycINFO, PubMed, Web of Science, and Google Scholar databases was conducted for publications through 30 July 2023. Citation tracking and reference tracking were also used, and this study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines. Results: Of 8908 studies initially retrieved, 57 met the selection criteria and were evaluated. The overall quality of the evidence, assessed using PEDro, was low. The evaluated studies included 1622 children with ASD, among which 517 were males, from level II to IV, and ranging in age from 3 to 17 years. Five types (physical activity interventions, motor skill interventions, hippotherapy, equine-assisted or simulated horse riding interventions, exergaming interventions, and physical education interventions) of motor development interventions were used, and 57 studies achieved some positive results for improvements in motor development among children with ASD. Furtherly, eight studies reported motor development acquisition, retention, or transfer. Children with ASD learn well from different types of instructors, including teachers, coaches, camp counselors, physical therapists, and peers. Conclusions: Motor skills and physical activity interventions improved motor development among children with ASD, the effect of which would continue until the end of the interventions. Full article

Low back pain (LBP) is a prevailing affliction among recreational and professional horse riders. It lowers performance and distracts from the development of the athlete. A lower incidence of LBP has been observed in the professional riding population despite higher training volumes. This paper aims to describe neuromuscular mechanisms through which advanced and novice riders attenuate the shockwave generated between the horse and rider. Six novice riders (age 24 ± 7 years), nine advanced riders (age 31 ± 5 years) and four horses (age 15 ± 3 years) took part in this study. Surface electromyographic activity of the riders’ trunk was recorded along with inertial data from the horses’ leg, saddle and vertebrae of the riders at walk, trot and canter. Analyses of variances revealed a superior shock attenuating ability of the advanced group (F (1,38) > 5.023, p < 0.03) as well as a higher overall muscle tone (F (1,488) > 9.80, p < 0.02). Cross correlation analyses between shock attenuation and electromyographic activity showed that groups differ mostly in timing rather than the intensity of muscle activation. This finding is of great interest for equestrian athletes and coaches, as it points to a greater importance of training muscular anticipation within the trunk stabilizers rather than overall muscle activation. Full article

The Equine Behaviour Assessment and Research Questionnaire (E-BARQ) is a questionnaire instrument developed to obtain quantitative data on the domestic equine triad of training, management, and behaviour of horses. The E-BARQ was developed to identify how changes in training and management impact behaviour over time, to define normal behaviour in horses, and to discover how to improve rider safety and horse welfare, leading to ethical equitation. During the development of the E-BARQ, we also investigated how best to motivate stakeholders to engage with this citizen science project. The pilot version of the E-BARQ collected qualitative data on respondents’ experience of the questionnaire. The pilot questionnaire was developed with the assistance of an international panel (with professional expertise in horse training, equitation science, veterinary science, equestrian coaching, welfare, animal behaviour, and elite-level riding), and was used to collect data on 1320 horses from approximately 1194 owner/caregiver respondents, with an option for respondents to provide free-text feedback. A Rotated Principal Component Analysis of the 218 behavioural, management, and training questionnaire items extracted a total of 65 rotated components. Thirty-six of the 65 rotated components demonstrated high internal reliability. Of the 218 questionnaire items, 43 items failed to reach the Rotated Principal Component Analysis criteria and were not included in the final version of the E-BARQ. Survey items that failed the Rotated Principal Component Analysis inclusion criteria were discarded if found to have a less than 85% response rate, or a variance of less than 1.3. Of those that survived the Rotated Principal Component Analysis, items were further assigned to horse temperament (17 rotated components), equitation (11 rotated components), and management and equipment (8 rotated components) groups. The feedback from respondents indicated the need for further items to be added to the questionnaire, resulting in a total of 214 items for the final E-BARQ survey. Many of these items were further grouped into question matrices, and the demographic items for horse and handler included, giving a final total of 97 questions on the E-BARQ questionnaire. These results provided content validity, showing that the questionnaire items were an acceptable representation of the entire horse training, management, and behavioural domain for the development of the final E-BARQ questionnaire. Full article

In this study, we classify four horse gaits (walk, sitting trot, rising trot, canter) of three breeds of horse (Jeju, Warmblood, and Thoroughbred) using a neuro-fuzzy classifier (NFC) of the Takagi-Sugeno-Kang (TSK) type from data information transformed by a wavelet packet (WP). The design of the NFC is accomplished by using a fuzzy c-means (FCM) clustering algorithm that can solve the problem of dimensionality increase due to the flexible scatter partitioning. For this purpose, we use the rider’s hip motion from the sensor information collected by inertial sensors as feature data for the classification of a horse’s gaits. Furthermore, we develop a coaching system under both real horse riding and simulator environments and propose a method for analyzing the rider’s motion. Using the results of the analysis, the rider can be coached in the correct motion corresponding to the classified gait. To construct a motion database, the data collected from 16 inertial sensors attached to a motion capture suit worn by one of the country’s top-level horse riding experts were used. Experiments using the original motion data and the transformed motion data were conducted to evaluate the classification performance using various classifiers. The experimental results revealed that the presented FCM-NFC showed a better accuracy performance (97.5%) than a neural network classifier (NNC), naive Bayesian classifier (NBC), and radial basis function network classifier (RBFNC) for the transformed motion data. Full article