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Acta anatomica1993; 146(2-3); 95-102; doi: 10.1159/000147428

Multi-body modelling and simulation of animal locomotion.

Abstract: Multi-body models of musculoskeletal systems can be used to determine internal forces from measured external forces and movements ('inverse dynamics') and to perform simulations of movements using muscle forces or activations as input ('direct dynamics'). Examples of 'direct' simulations of movements in the horse are presented. With a model of the equine hindlimb, the function of the 'passive stay apparatus' could be explained. A model of the forelimb was used to determine force distributions in the digital flexor tendons, and to experiment with various methods to change the force distribution. Simulations of this type are valuable tools in basic research on functional anatomy and aetiology of injuries. An application with much future potential is the optimization of sports performances using simulation methods.
Publication Date: 1993-01-01 PubMed ID: 8470472DOI: 10.1159/000147428Google Scholar: Lookup
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  • Journal Article
  • Research Support
  • Non-U.S. Gov't

Summary

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This research article explores the use of multi-body models to understand and simulate animal locomotion, with a primary focus on horses. These models help explain the internal mechanisms at work during movement, which can aid in injury prevention and optimizing sports performances.

Objective of the Research

  • The primary goal of the research is to demonstrate the function and benefits of multi-body models of musculoskeletal systems in understanding animal locomotion. In this context, animal locomotion pertains to the movement of horses.

Methodology

  • Through the creation and deployment of multi-body models of the musculoskeletal systems, the mechanism of action of internal forces, in response to external forces and movements, was studied (‘inverse dynamics’).
  • These models were also used to simulate movements in horses using muscle forces or activations as the point of focus (‘direct dynamics’).
  • Two key examples were presented; a model of the horse’s hindlimb to explain the function of the ‘passive stay apparatus’, and a forelimb model to determine force distribution within the digital flexor tendons.
  • Within the forelimb model, various methods were experimented with to test how they could alter the force distribution.

Findings

  • The researchers found that these types of simulations are valuable tools in the basic research on functional anatomy and the origin (aetiology) of injuries in animals. By understanding how the forces are distributed and how the muscles act during movement, it could assist in the development of injury prevention methods.

Future Applications

  • A key future application of this research is the optimization of sports performances. By understanding animal locomotion on a granular level, it could provide insights into how to optimize performance, especially in equine sports where the efficiency, speed, and strength of horses are vital to performance.

Cite This Article

APA
van den Bogert AJ, Schamhardt HC. (1993). Multi-body modelling and simulation of animal locomotion. Acta Anat (Basel), 146(2-3), 95-102. https://doi.org/10.1159/000147428

Publication

ISSN: 0001-5180
NlmUniqueID: 0370272
Country: Switzerland
Language: English
Volume: 146
Issue: 2-3
Pages: 95-102

Researcher Affiliations

van den Bogert, A J
  • Human Performance Laboratory, Faculty of Physical Education, University of Calgary, Alta., Canada.
Schamhardt, H C

    MeSH Terms

    • Animals
    • Computer Simulation
    • Horses
    • Locomotion / physiology
    • Models, Biological
    • Sports Medicine / methods

    Citations

    This article has been cited 3 times.
    1. Cleather DJ, Bull AM. The development of a segment-based musculoskeletal model of the lower limb: introducing FreeBody. R Soc Open Sci 2015 Jun;2(6):140449.
      doi: 10.1098/rsos.140449pubmed: 26543569google scholar: lookup
    2. van den Bogert AJ, Blana D, Heinrich D. Implicit methods for efficient musculoskeletal simulation and optimal control. Procedia IUTAM 2011 Jan 1;2(2011):297-316.
      doi: 10.1016/j.piutam.2011.04.027pubmed: 22102983google scholar: lookup
    3. van Bijlert PA, Geijtenbeek T, Smit IH, Schulp AS, Bates KT. Muscle-Driven Predictive Physics Simulations of Quadrupedal Locomotion in the Horse. Integr Comp Biol 2024 Sep 27;64(3):694-714.
      doi: 10.1093/icb/icae095pubmed: 39003243google scholar: lookup