This paper presents a structurally based modeling framework to characterize the structure-function relation in skin tissues, based upon biaxial tensile experiments performed in vitro on porcine skin. Equi-axial deformations were imposed by stretching circular skin specimens uniformly along twelve directions, and the resultant loads at the membrane attachment points were measured. Displacement fields at each deformation step were tracked using an image 2D cross-correlation technique. A modeling framework was developed to simulate the experiments, whereby measured forces were applied to finite element models that were created to represent the geometry and structure of the tissue samples. Parameters of a structurally based constitutive relation were then identified using nonlinear optimization. Results showed that the ground matrix stiffness ranged from 5 to 32 kPa, fiber orientation mean from 2 to 13(◦) from the torso midline, fiber undulation mean from 1.04 to 1.34 and collagen fiber stiffness from 48 to 366 MPa. It was concluded that the objective function was highly sensitive to the mean orientation and that a priori information about fiber orientation mean was important for the reliable identification of constitutive parameters.
The characterization of skin mechanics has many clinical implications and has been an active area of research for the past few decades. Biomechanical models have evolved from earlier empirical models to state-of-the-art structural models that provide linkage between tissue microstructure and macroscopic stress-strain response. To maximize the accuracy and predictive capabilities of such computational models, there is a need to reliably identify often a large number of unknown model parameters. This is critically dependent on the availability of experimental data that cover an extensive range of different deformation modes, and quantification of internal structural features, such as collagen orientation. To this end, future challenges should include the ongoing development of noninvasive instrumentation and imaging modalities for in vivo skin measurements. We highlight the important concept of tightly integrating computational models, instrumentation, and imaging modalities into a single platform to investigate skin biomechanics.
We demonstrate that two parameters of this distribution (the mean and spread parameter) may be directly determined using CLSM image analysis. An important advantage of this approach is that model parameters can be estimated directly from observable microstructural features.
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