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Analyzing Uncertainty of an Ankle Joint Model with Genetic Algorithm.

Adam Ciszkiewicz1

  • 1Institute of Applied Mechanics, Cracow University of Technology, 31-155 Cracow, Poland.

Materials (Basel, Switzerland)
|March 12, 2020
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Summary

This study introduces a genetic algorithm to analyze uncertainty in biomechanical models by optimizing adversarial models. The method revealed significant differences in ankle joint angular displacements despite visually similar model structures.

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material and geometric parametersmultibody systemoptimizationsensitivitystatics

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Area of Science:

  • Biomechanics
  • Computational Biology
  • Numerical Analysis

Background:

  • Biomechanical models traditionally use fixed parameters.
  • A paradigm shift suggests parameters should be treated as random variables, necessitating new numerical methods for uncertainty analysis.

Purpose of the Study:

  • To introduce and verify a genetic algorithm for uncertainty analysis in biomechanical modeling.
  • To apply this novel method to an ankle joint model with numerous parameters and flexible links.

Main Methods:

  • Encoding two adversarial models within a single decision variable vector.
  • Concurrently optimizing these models to maximize the difference between their outputs.
  • Applying the procedure to an ankle joint model with 43 parameters and flexible links, with specified bounds for geometrical and material parameters.

Main Results:

  • The genetic algorithm successfully analyzed uncertainty in the biomechanical model.
  • Adversarial structures generated by the algorithm were visually indistinguishable.
  • Despite visual similarity, the models exhibited up to 38.52% difference in angular displacements.

Conclusions:

  • The proposed genetic algorithm offers a general and effective approach for biomechanical model uncertainty analysis.
  • This method can identify significant parameter uncertainties even when model structures appear similar.
  • Further research is needed to explore the computational efficiency and broader applicability of this technique.