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Integrative and comparative biology2024; 64(3); 694-714; doi: 10.1093/icb/icae095

Muscle-Driven Predictive Physics Simulations of Quadrupedal Locomotion in the Horse.

Abstract: Musculoskeletal simulations can provide insights into the underlying mechanisms that govern animal locomotion. In this study, we describe the development of a new musculoskeletal model of the horse, and to our knowledge present the first fully muscle-driven, predictive simulations of equine locomotion. Our goal was to simulate a model that captures only the gross musculoskeletal structure of a horse, without specialized morphological features. We mostly present simulations acquired using feedforward control, without state feedback ("top-down control"). Without using kinematics or motion capture data as an input, we have simulated a variety of gaits that are commonly used by horses (walk, pace, trot, tölt, and collected gallop). We also found a selection of gaits that are not normally seen in horses (half bound, extended gallop, ambling). Due to the clinical relevance of the trot, we performed a tracking simulation that included empirical joint angle deviations in the cost function. To further demonstrate the flexibility of our model, we also present a simulation acquired using spinal feedback control, where muscle control signals are wholly determined by gait kinematics. Despite simplifications to the musculature, simulated footfalls and ground reaction forces followed empirical patterns. In the tracking simulation, kinematics improved with respect to the fully predictive simulations, and muscle activations showed a reasonable correspondence to electromyographic signals, although we did not predict any anticipatory firing of muscles. When sequentially increasing the target speed, our simulations spontaneously predicted walk-to-run transitions at the empirically determined speed. However, predicted stride lengths were too short over nearly the entire speed range unless explicitly prescribed in the controller, and we also did not recover spontaneous transitions to asymmetric gaits such as galloping. Taken together, our model performed adequately when simulating individual gaits, but our simulation workflow was not able to capture all aspects of gait selection. We point out certain aspects of our workflow that may have caused this, including anatomical simplifications and the use of massless Hill-type actuators. Our model is an extensible, generalized horse model, with considerable scope for adding anatomical complexity. This project is intended as a starting point for continual development of the model and code that we make available in extensible open-source formats.
© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology.
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Publication Date: 2024-07-14 PubMed ID: 39003243PubMed Central: PMC11428545DOI: 10.1093/icb/icae095Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research study explores the use of musculoskeletal simulations to understand how horses move. The researchers developed a new model that can predict various horse gaits, such as walk, trot and gallop, indicating the potential usefulness of the model in studying animal locomotion.

Development of a New Musculoskeletal Model

  • The researchers developed a new musculoskeletal model that simulates the gross structure of a horse, without considering the specialized morphological features.
  • This model resulted in various simulations of horse gaits including walk, pace, trot, tölt, and collected gallop, using mostly feedforward control, a method that doesn’t rely on state feedback or “top-down control”.
  • The team went beyond common gaits and experimented with uncommon ones such as half bound, extended gallop and ambling, demonstrating the model’s flexibility.

Specific Applications of the Model

  • The study also featured a tracking simulation of a trot, which is clinically relevant, showing that the model could be incorporated in the analysis of horse locomotion for health and clinical applications.
  • In this tracking simulation, empirical joint angle deviations were included in the cost function. Simulated footfalls and ground reaction forces aligned with empirical patterns, which indicates the accuracy of the model despite simplifications to the musculature.

Model Limitations

  • The study noted that the model did not predict anticipatory muscle firing and that stride lengths were too short across almost all speeds unless explicitly set in the controller.
  • The model also fell short in predicting transitions to asymmetric gaits, like galloping.
  • This suggests that while the model can simulate individual gaits, it falls short in capturing aspects of gait selection. The authors attribute these shortcomings to the simplification of the anatomy and the use of massless Hill-type actuators.

Future Potential and Extensions

  • The study positions the model as a starter tool for more extensive and continual development. It invites further research to address the model’s weak points, such as anatomical complexity.
  • In conclusion, this horse musculoskeletal model is a versatile tool that has promising potential for further research in understanding animal locomotion. The team has made the model and the code readily available in open-source format for other researchers to utilise and enhance.

Cite This Article

APA
van Bijlert PA, Geijtenbeek T, Smit IH, Schulp AS, Bates KT. (2024). Muscle-Driven Predictive Physics Simulations of Quadrupedal Locomotion in the Horse. Integr Comp Biol, 64(3), 694-714. https://doi.org/10.1093/icb/icae095

Publication

Integrative and comparative biology
ISSN: 1557-7023
NlmUniqueID: 101152341
Country: England
Language: English
Volume: 64
Issue: 3
Pages: 694-714

Researcher Affiliations

van Bijlert, Pasha A
  • Department of Earth Sciences, Faculty of Geosciences, Utrecht University, Vening Meinesz Building A, Princetonlaan 8A, 3584 CB Utrecht, the Netherlands.
  • Vertebrate evolution, development and ecology, Naturalis Biodiversity Center, Darwinweg 2, 2333 CR Leiden, the Netherlands.
Geijtenbeek, Thomas
  • Goatstream, Utrecht, the Netherlands.
Smit, Ineke H
  • Department of Equine Musculoskeletal Biology, Faculty of Veterinary Sciences, Utrecht University, Yalelaan 112-114, 3584 CM Utrecht, the Netherlands.
Schulp, Anne S
  • Department of Earth Sciences, Faculty of Geosciences, Utrecht University, Vening Meinesz Building A, Princetonlaan 8A, 3584 CB Utrecht, the Netherlands.
  • Vertebrate evolution, development and ecology, Naturalis Biodiversity Center, Darwinweg 2, 2333 CR Leiden, the Netherlands.
Bates, Karl T
  • Department of Musculoskeletal & Ageing Science, Institute of Life Course & Medical Sciences, University of Liverpool, The William Henry Duncan Building, 6 West Derby Street, Liverpool L7 8TX, UK.

MeSH Terms

  • Animals
  • Horses / physiology
  • Biomechanical Phenomena
  • Locomotion / physiology
  • Models, Biological
  • Muscle, Skeletal / physiology
  • Gait / physiology
  • Computer Simulation
  • Hindlimb / physiology

Grant Funding

  • EA740 / Company of Biologists

Conflict of Interest Statement

Thomas Geijtenbeek is the author and proprietor of the Hyfydy simulation software that we used to perform the feedback-controlled simulations. This manuscript focused on model development, not simulator performance, so this had no bearing on the interpretation of our results. We declare no further possible conflicts of interests.

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Citations

This article has been cited 4 times.
  1. Fleischmann S, Shanbhag J, Miehling J, Wartzack S, Ong C, Eskofier BM, Koelewijn AD. A model of the cerebellum generates gait adaptations in a reflex-based neuromusculoskeletal model during split-belt walking. bioRxiv 2025 Nov 24;.
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