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Spatial extension of a bone remodeling dynamics model and its finite element analysis.

Jacobo G BaldonedoJosé R FernándezAbraham Segade
Published in: International journal for numerical methods in biomedical engineering (2021)
There are many works dealing with the dynamics of bone remodeling, proposing increasingly complex and complete models. In the recent years, the efforts started to focus on developing models that not only reproduce the temporal evolution, but also include the spatial aspects of this phenomenon. In this work, we propose the spatial extension of an existing model that includes the dynamics of osteocytes. The spatial dependence is modeled in terms of a linear diffusion, as proposed in previous works dealing with related problems. The resulting model is then written in its variational form, and fully discretized using the well-known finite element method and a combination of the implicit and explicit Euler schemes. The numerical algorithm is then analyzed, proving some a priori error estimates and its linear convergence. Finally, we extend the examples already published for the temporal model to one and two dimensions, showing the dynamics of the solution in the spatial domain.
Keyphrases
  • mental health
  • machine learning
  • bone mineral density
  • deep learning
  • randomized controlled trial
  • body composition
  • bone loss