Master of Science (MS)
Electrical and Computer Engineering
Therapeutic horseback riding is a common component of physical therapy programs. Quantification of the horse back forces will provide vital information to match therapeutic riders with equine partners. To meet this medical need, a model to quantify the horse back forces from ground reaction forces was developed to test the hypothesis that the forces transferred to a static weight on the horse’s back can be predicted given horse breed and weight. Simultaneous, real time kinetic, kinematic, and back force data on a static weight were collected from 7 adult horses: 3 thoroughbreds, 3 quarter horses, and 1 paso fino. An integrated system consisting of a force platform, an active motion detection system and wireless force transducers were used. Data was collected from a minimum of four successful trials from all horses at a walk (1.3-2.0 m/s). Inverse dynamic analysis was used to calculate the fore and hind limb joint forces to the shoulder and hip, taking into consideration all 4 limbs’ motion per stride cycle. Virtual segments were created to model the equine back as a series of springs and dampers and joined to the limbs. Calculated forces from the inverse dynamics analysis were then input to the spring-damper model sequentially and at the same frequency as data collection. The energy absorption coefficients were derived by aligning the model output forces of the fore- and hind limb data with measured back forces. Horse back forces were simulated with different coefficients for each breed, and specifically for each horse. . Simulated results had a significant positive correlation (r = 0.81±0.04, p <0.001) with forces measured directly on the back. The data from this investigation will contribute to mechanisms to predict forces experienced by the rider during horse motion to advance the science of therapeutic riding.
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Kaidapuram, Laxmi Raghunandana, "Development and validation of biomechanical models to quantify horse back forces at the walk in three horse breeds" (2011). LSU Master's Theses. 1661.