Head and neck positions influence significantly the kinematics of the ridden horse. It is important for riders and trainers to be aware of these effects in dressage training.
We live in a world with an ever-increasing ageing population. Studying healthy ageing and reducing the socioeconomic impact of age-related diseases is a key research priority for the industrialised and developing countries, along with a better mechanistic understanding of the physiology and pathophysiology of ageing that occurs in a number of age-related musculoskeletal disorders. Arthritis and musculoskeletal disorders constitute a major cause of disability and morbidity globally and result in enormous costs for our health and social-care systems. By gaining a better understanding of healthy musculoskeletal ageing and the risk factors associated with premature ageing and senescence, we can provide better care and develop new and better-targeted therapies for common musculoskeletal disorders. This review is the outcome of a two-day multidisciplinary, international workshop sponsored by the Institute of Advanced Studies entitled "Musculoskeletal Health in the 21st Century" and held at the University of Surrey from 30th June-1st July 2015. The aim of this narrative review is to summarise current knowledge of musculoskeletal health, ageing and disease and highlight strategies for prevention and reducing the impact of common musculoskeletal diseases.
SUMMARY The purpose of this study was to determine whether individual limb forces could be calculated accurately from kinematics of trotting and walking horses. We collected kinematic data and measured vertical ground reaction forces on the individual limbs of seven Warmblood dressage horses, trotting at 3.4 m s–1 and walking at 1.6 m s–1 on a treadmill. First, using a segmental model, we calculated from kinematics the total ground reaction force vector and its moment arm relative to each of the hoofs. Second, for phases in which the body was supported by only two limbs, we calculated the individual reaction forces on these limbs. Third, we assumed that the distal limbs operated as linear springs, and determined their force–length relationships using calculated individual limb forces at trot. Finally, we calculated individual limb force–time histories from distal limb lengths. A good correspondence was obtained between calculated and measured individual limb forces. At trot, the average peak vertical reaction force on the forelimb was calculated to be 11.5±0.9 N kg–1 and measured to be 11.7±0.9 N kg–1, and for the hindlimb these values were 9.8±0.7 N kg–1 and 10.0±0.6 N kg–1,respectively. At walk, the average peak vertical reaction force on the forelimb was calculated to be 6.9±0.5 N kg–1 and measured to be 7.1±0.3 N kg–1, and for the hindlimb these values were 4.8±0.5 N kg–1 and 4.7±0.3 N kg–1, respectively. It was concluded that the proposed method of calculating individual limb reaction forces is sufficiently accurate to detect changes in loading reported in the literature for mild to moderate lameness at trot.
Vertebral kinematics during treadmill locomotion is not identical to over ground locomotion, but the differences are minor. During treadmill locomotion lumbar motion is less, and caution should be therefore taken when interpreting lumbar kinematics.
Back problems are important contributors to poor performance in sport horses. It has been shown that kinematic analysis can differentiate horses with back problems from asymptomatic horses. The underlying mechanism can, however, only be identified in a uniform, experimental setting. Our aim was to determine if induction of back pain in a well-defined site would result in a consistent change in back movement. Back kinematics were recorded at a walk and trot on a treadmill. Unilateral back pain was then induced by injecting lactic acid into the left longissimus dorsi muscle. Additional measurements were done subsequent to the injections. Data were captured during steady state locomotion at 240 Hz using an infrared-based gait analysis system. After the injections, the caudal thoracic back was more extended at both gaits. The back was also bent more to the left at both gaits. However, at the walk, there was a reversed pattern after a week with bending of the back to the unaffected side. Horses with identical back injuries appear to show similar changes in their back kinematics, as compared to the asymptomatic condition. Unilateral back pain seems to result in an increased extension of the back, as well as compensatory lateral movements. Back movements are complex and subtle, and changes are difficult to detect with the human eye. Present-day gait analysis systems can identify changes in the back movement, and knowledge of the relationship between such changes and the site of injury will be of help in better localising and diagnosing disorders of the equine back.
Early detection of disease by an animal owner may motivate them to seek early veterinary advice. Presentation before a more advanced clinical manifestation is evident could lead to more effective treatment and thus benefit the animal’s health and welfare. Accelerometers are able to detect changes in specific activities or behaviours, thus indicating early signs of possible adverse health events. The objective of this validation study was to determine whether the detection of eight behavioural states: walk, trot, canter/gallop, sleep, static/inactive, eat, drink, and headshake, by an accelerometer device was sufficiently accurate to be useful in a clinical setting. This fully independent external validation estimated the accuracy of a specific triaxial, collar-mounted accelerometer on a second-by second basis in 51 healthy dogs of different breeds, aged between 6 months and 13 years, weighing >10 kg. The overall diagnostic effectiveness was estimated as: % record correctly classified of > 95% in walk, trot, canter/gallop, eat, drink and headshake and >90% in sleep and static/inactive. The positive predictive values ranged from 93–100%, while the negative predictive values ranged from 96–100%, with exception of static/inactive (86%).This was probably because dogs were placed in unfamiliar kennels where they did not exhibit their typical resting behaviour. The device is worn on a collar, making its use feasible for anyone wanting to monitor their dog’s behaviour. The high accuracy in detecting various kinds of behaviour appears promising in assessing canine health and welfare states.
It is widely accepted that canine breeds stand and move differently. The prevalence of various musculoskeletal disorders such as hip and elbow dysplasia is also different between breeds. German shepherd dog (GSD) and Labrador retriever dog (LRD) are two large breeds with different conformations that have high prevalence of these disorders. This study quantifies the movement and standing posture of twelve healthy GSDs and twelve healthy LRDs to identify biomechanical similarities and differences that may be linked to sub-optimal hip and elbow mechanics. A pressure walkway and a motion capture system obtained measures of kinetics, kinematics and conformation during standing and trot. During standing, LRDs carry a greater percentage of the weight on the forelimbs (69%±5% vs. GSDs: 62% ±2%, p<0.001) and their body Centre of Pressure (CoP) is located more cranially (p<0.001). GSDs had a greater pelvic tilt (79˚±8 vs. 66˚±9˚, p = 0.004), more flexed stifles (44˚±9˚vs. LRDs: 34˚±10˚, p<0.05) and hocks (58˚±11˚vs. 26˚±9˚, p<0.01) and more extended hips (-10˚±11˚vs. 30˚±12˚, p<0.001). During trot, the GSDs' CoP had a longer anterior-posterior trajectory (151%±22% vs. LRDs: 93%±25% of the withers height, p<0.001). Stride parameters and loading of limbs were similar when normalised to the size and weight of the dog, respectively. The LRDs had a more extended thoracolumbar angle (p<0.001) and a less flexed lumbosacral angle (p<0.05). The LRDs' hip remained flexed during trot whereas the GSDs' hip joint was less flexed during swing (p<0.001) and more extended in late stance and early swing (p<0.001). In conclusion, the LRDs and GSDs differ in the way they stand and move and this would result in different loading pattern of the joints. Further investigation is required to determine the extent to which biomechanical differences are linked to musculoskeletal problems presented clinically.
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