Tutorial video for: A toolbox for the retrodeformation and muscle reconstruction of fossil specimens in Blender
Herbst, Eva C. et al. (2022), Tutorial video for: A toolbox for the retrodeformation and muscle reconstruction of fossil specimens in Blender, Dryad, Dataset, https://doi.org/10.5061/dryad.qjq2bvqk2
Accurate muscle reconstructions can offer new information on the anatomy of fossil organisms and are also important for biomechanical analysis (multibody dynamics and finite element analysis). For the sake of simplicity, muscles are often modeled as point-to-point strands or frustra (cut off cones) in biomechanical models. However, there are cases in which it is useful to model the muscle morphology in 3D, to better examine the effects of muscle shape and size. This is especially important for fossil analyses, where muscle force is estimated from the reconstructed muscle morphology (rather than based on data collected in vivo). The two main aims of this paper are as follows. First, we created a new interactive tool in the free open access software Blender to enable interactive 3D modeling of muscles. This approach can be applied to both palaeontological and human biomechanics research to generate muscle force magnitudes and lines of action for finite element analysis. Second, we provide a guide on how to use existing Blender tools to reconstruct distorted or incomplete specimens. This guide is aimed at palaeontologists but can also be used by anatomists working with damaged specimens or to test functional implication of hypothetical morphologies.
This video demonstrates use of the Blender add-on. The Python code for the add-on, as well as installation instructions, can be found on Github (https://github.com/evaherbst/MyoGenerator). If using this add-on, please cite our paper as well as the Zenodo DOI for the Github release (doi.org/10.5281/zenodo.6914448).
Note that this add-on has been tested and works on v. 2.91.0 - 2.93.0 of Blender. Older or newer versions may break the code.
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Award: 31003A_179401