08 · msc research · university of cape town
Myocardial Mechanics
Measuring how heart muscle deforms, and making the material model prove it.
100+
tissue samples tested
80+
imaging datasets analysed
10x10
mm specimens
1
finite-element solver, from scratch
/ interactive · shape the material model
try it, everything responds
Push k₂ up and watch the exponential toe-to-heel stiffening appear; swing the fiber angle toward 45° and the two directions converge, and the anisotropy vanishes.
cauchy stress vs stretch · equibiaxial · illustrative units
This is the shape of soft-tissue mechanics: nearly compliant at low stretch, then exponentially stiff as collagen fibers recruit, and stiffer along the fiber direction than across it. In the research, these parameters weren't sliders: they were fitted to full-field DIC strain measurements from ~35 real myocardium samples, with true stress computed from histology-informed thickness, with over 100 samples and 80+ DIC datasets in.
A note on this demo. Every figure, name and data point here is invented for illustration. No client data, real economics or production configuration appears anywhere on this site. What is real is the machinery: the calculations, the rules and the logic running in your browser are the same ones the production system uses, so the demo behaves exactly as the real thing behaves.
What it is
/ in plain terms
Stretching tiny 10 by 10 millimetre pieces of heart muscle in two directions at once, while cameras track exactly how the tissue deforms, then fitting mathematical models that describe how heart muscle behaves as a material. Groundwork for research into treating heart-attack damage.
Completed MSc research at the University of Cape Town: experimental characterisation of myocardial tissue from sample preparation through to constitutive modelling. Planar biaxial testing (stretching a specimen along two axes simultaneously) of 10x10 mm specimens, with Digital Image Correlation, a camera technique that tracks a speckle pattern painted on the tissue to measure deformation across the whole surface. Custom 3D-printed apparatus made the two techniques coexist, and a Python pipeline turns the images into true stress, regional strain maps and fitted Gasser-Ogden-Holzapfel material parameters. The rigor that now goes into parity tests started here, where a wrong number is not a bad dashboard but bad science.
MSc candidate, Mechanical and Biomedical Engineering, working with engineering and medical teams.
The load-bearing details
- 01Refined biaxial testing protocols for soft tissue, using full-field optical measurement instead of trusting how far the grips moved.
- 02Designed and 3D-printed custom apparatus components so that the camera system and the stretching rig could work together on small, fragile specimens.
- 03Tested over 100 myocardial tissue samples and analysed over 80 imaging datasets to establish and iterate the methodology toward reliable data.
- 04Built the analysis pipeline in Python: true-stress computation, regional strain mapping, histology-informed thickness analysis and material-model fitting.
- 05Separately built a finite-element solver (the standard engineering technique for simulating how structures deform under load) from scratch in Python, covering linear and nonlinear elasticity, heat conduction and near-incompressibility.
- 06Laid the groundwork for studies assessing hydrogel treatments for heart-attack damage in an infarcted rat model.