Race surface model development in a musculoskeletal modelling environment

Musculoskeletal injury is the leading cause of racehorse attrition and fatalities. Many factors have been implicated in racehorse musculoskeletal injury, including race surface. Race surface material has been shown to affect ground reaction forces applied to the hoof, limb kinematics, surface dynamic mechanical behavior, and incidence of injury. The optimal interaction of the racehorse hoof with the race surface during locomotion is unknown. Further, the effect of surface on limb biomechanics has only been examined by installing a surface and observing horses during gallop across the surface. Installation of new surfaces is financially costly, results in lost training time, and does not allow a thorough evaluation of possible mechanisms of injury associated with surface/hoof interactions. A computational equine limb-surface simulation model is needed to examine racehorse limb biomechanics on virtual surfaces, and further to consider the possible musculoskeletal consequences of a surface, prior to installation. A racetrack surface model was developed for use in musculoskeletal modelling and simulation applications. Surface parameters were determined by fitting empirical force, displacement, and velocity data collected during vertical and angled dynamic soil tests using a track-testing device. Simulations of the dynamic soil tests on the surface closely reproduced measured load and displacement data. In the future, this surface model may be incorporated in racehorse limb simulations of gallop using virtual surface parameters to predict the optimal surface mechanical properties for musculoskeletal health during racing and training.
© Copyright 2014 Procedia Engineering. Elsevier. All rights reserved.

Bibliographic Details
Subjects:
Notations:technical and natural sciences technical sports biological and medical sciences
Published in:Procedia Engineering
Language:English
Published: 2014
Online Access:http://doi.org/10.1016/j.proeng.2014.06.155
Volume:72
Pages:913-918
Document types:article
Level:advanced