Description

Understanding the mechanical function of facial muscles during expressions and mimetic movements is essential for establishing a quantitative diagnosis and defining a personalized functional rehabilitation strategy in patients with facial paralysis or face transplantation. Finite element models have been developed to investigate the activation, contraction, and coordination of facial muscles during facial expressions [1,2]. However, generating a compatible mesh that ensures numerical stabilities and convergence remains a scientific challenge. In particular, the complex geometry derived from medical imaging and the integration of active multi-scale soft tissue constitutive laws require the generation of high-quality adaptive meshes considering the anisotropic nature of different materials.
The objective of this PhD project is to develop an adaptive meshing of the human face incorporating complex geometry derived from medical imaging and multiscale behavior of soft tissues. To scope with these complex constraints, different advanced meshing procedures such as mesh simplification to handle contact interface, voxel smoothing, iterative smoothing and mesh size adaptation will be studied [3,4]. Physical constraints related to the facial muscle contraction patterns (longitudinal and circumferential) and multi-scale soft tissue constitutive laws will be integrated. The developed meshing approach will be tested on the development of a digital twin of the human face derived from MRI images. Facial expressions will be simulated to evaluate the quality of the meshed structures to ensure the numerical stabilities and convergence of the results. The different steps of the project will to perform 1) the state of the art of meshing for complex biomechanical systems, 2) the development and implementation of the adaptive mesh, 3) the integration of the developed adaptive mesh onto the digital twin of the human face derived from MRI and 4) the simulations to evaluate the quality of the developed adaptive mesh.

Skills required

The candidate is a solid or fluid mechanics engineer/master with strong skills in numerical mechanics and programming (C, C++, Python). Mechanical or biomechanical background.

Bibliography

[1] Fan A-F., Dakpé S., Dao T.T, Pouletaut P., Rachik M., Ho Ba Tho M-C (2017) MRI-based finite element modeling of facial mimics: a case study on the paired zygomaticus major muscles. Comput Methods Biomech Biomed Engin 20(9):919-928. https://doi.org/10.1080/10255842.2017.1305363
[2] Dao TT, Fan AX, Dakpe S, Pouletaut P, Rachik M, Ho Ba Tho MC (2018). Image-based skeletal muscle coordination: case study on a subject specific facial mimic simulation. Journal of Mechanics in Medicine and Biology https://doi.org/10.1142/S0219519418500203
[3] Fourrier G., Rassineux, A., Leroy, F. H., Hirsekorn, M., Fagiano, C., & Baranger, E. (2023). Automated conformal mesh generation chain for woven composites based on CT-scan images with low contrasts. Composite Structures, 116673 https://doi.org/10.1016/j.compstruct.2023.116673

[4] Rassineux, A. (2021). Robust conformal adaptive meshing of complex textile composites unit cells. Composite Structures, 114740 https://doi.org/10.1016/j.compstruct.2021.114740

Keywords

Mesh generation, Finite element, Mechanical behavior, Medical images