Modeling equine race surface vertical mechanical behaviors in a musculoskeletal modeling environment.
Abstract: Race surfaces have been associated with the incidence of racehorse musculoskeletal injury, the leading cause of racehorse attrition. Optimal race surface mechanical behaviors that minimize injury risk are unknown. Computational models are an economical method to determine optimal mechanical behaviors. Previously developed equine musculoskeletal models utilized ground reaction floor models designed to simulate a stiff, smooth floor appropriate for a human gait laboratory. Our objective was to develop a computational race surface model (two force-displacement functions, one linear and one nonlinear) that reproduced experimental race surface mechanical behaviors for incorporation in equine musculoskeletal models. Soil impact tests were simulated in a musculoskeletal modeling environment and compared to experimental force and displacement data collected during initial and repeat impacts at two racetracks with differing race surfaces - (i) dirt and (ii) synthetic. Best-fit model coefficients (7 total) were compared between surface types and initial and repeat impacts using a mixed model ANCOVA. Model simulation results closely matched empirical force, displacement and velocity data (Mean R(2)=0.930-0.997). Many model coefficients were statistically different between surface types and impacts. Principal component analysis of model coefficients showed systematic differences based on surface type and impact. In the future, the race surface model may be used in conjunction with previously developed the equine musculoskeletal models to understand the effects of race surface mechanical behaviors on limb dynamics, and determine race surface mechanical behaviors that reduce the incidence of racehorse musculoskeletal injury through modulation of limb dynamics.
Copyright © 2015 Elsevier Ltd. All rights reserved.
Publication Date: 2015-01-19 PubMed ID: 25634662DOI: 10.1016/j.jbiomech.2015.01.006Google Scholar: Lookup
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- Journal Article
- Research Support
- Non-U.S. Gov't
Summary
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The research focuses on analyzing the impact of different racing surfaces on horse-related injuries. By using computational modeling, the study aims to develop an optimal model of the racing surface that can reduce the risk of equine musculoskeletal injury.
Objective and Methodology
- The primary aim of the research was to create a computer model of a racing surface that can accurately re-enact race surface mechanical behaviors. The motivation stems from the need to understand the correlation between the racing surface and the high incidence of injuries suffered by racehorses.
- Modeling in this way is economical yet effective and provides accurate insights into the impact of track surfaces on horse injuries. From the model, two force-displacement functions, one linear and another non-linear, were developed to imitate the race surface’s mechanical behavior.
- Experimental data from soil impact tests were gathered during initial and repeat impacts at two racetracks, one with a dirt surface and the other synthetic. The simulation results from the computer model were then compared with these test findings.
Results and Conclusions
- The computational model performed well in simulating the experimental data, showing a close match with empirical force, displacement, and velocity data, and thereby validating the model.
- Statistical differences in the model coefficients between surface types and impacts were detected, reflecting the real-world variability and confirming that the type of racing track surface and the number of impacts affect the mechanical responses.
- According to the results of the principal component analysis, these differences in model coefficients were systematic, further emphasizing the importance of considering surface type and impact when studying racehorse injuries.
Future Implications
- The race surface model can now be combined with previously developed equine musculoskeletal models to understand the impact of racing surface behaviors on limb dynamics.
- In the long run, this integration could help researchers and racing authorities identify racing surface properties that minimize the risk of equine injuries by regulating limb dynamics, leading to safer horse racing practices and environments.
Cite This Article
APA
Symons JE, Fyhrie DP, Hawkins DA, Upadhyaya SK, Stover SM.
(2015).
Modeling equine race surface vertical mechanical behaviors in a musculoskeletal modeling environment.
J Biomech, 48(4), 566-572.
https://doi.org/10.1016/j.jbiomech.2015.01.006 Publication
Researcher Affiliations
- Biomedical Engineering Graduate Group, University of California - Davis, Davis, CA, USA; Department of Anatomy, Physiology and Cell Biology, University of California - Davis School of Veterinary Medicine, Davis, CA, USA.
- Biomedical Engineering Graduate Group, University of California - Davis, Davis, CA, USA; Department of Orthopaedic Surgery, University of California - Davis Medical Center Sacramento, CA, USA.
- Biomedical Engineering Graduate Group, University of California - Davis, Davis, CA, USA; Department of Neurobiology, Physiology and Behavior, University of California - Davis, Davis, CA, USA.
- Department of Biological and Agricultural Engineering, University of California - Davis, Davis, CA, USA.
- Biomedical Engineering Graduate Group, University of California - Davis, Davis, CA, USA; Department of Anatomy, Physiology and Cell Biology, University of California - Davis School of Veterinary Medicine, Davis, CA, USA. Electronic address: smstover@ucdavis.edu.
MeSH Terms
- Animals
- Behavior, Animal / physiology
- Biomechanical Phenomena / physiology
- Computer Simulation
- Environment
- Forelimb / physiology
- Gait / physiology
- Hoof and Claw / physiology
- Horses / physiology
- Mechanical Phenomena
- Models, Biological
- Musculoskeletal Physiological Phenomena
- Running / physiology
- Soil
Citations
This article has been cited 1 times.- Harrison SM, Whitton RC, Stover SM, Symons JE, Cleary PW. A Coupled Biomechanical-Smoothed Particle Hydrodynamics Model for Horse Racing Tracks.. Front Bioeng Biotechnol 2022;10:766748.
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