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Related Experiment Video

Updated: May 25, 2026

Characterizing Multiscale Mechanical Properties of Brain Tissue Using Atomic Force Microscopy, Impact Indentation, and Rheometry

Characterizing Multiscale Mechanical Properties of Brain Tissue Using Atomic Force Microscopy, Impact Indentation, and Rheometry

Published on: September 6, 2016

Constitutive model for brain tissue under finite compression.

Kaveh Laksari¹, Mehdi Shafieian, Kurosh Darvish

¹Department of Mechanical Engineering, Temple University, Philadelphia, PA 19122, USA.

Journal of Biomechanics

|January 28, 2012

Summary

This study developed a viscoelastic model for bovine brain tissue under compression, validating quasi-linear viscoelasticity and using generalized Rivlin and Ogden models to capture its mechanical behavior accurately.

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Characterizing Multiscale Mechanical Properties of Brain Tissue Using Atomic Force Microscopy, Impact Indentation, and Rheometry

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A Coupled Experiment-finite Element Modeling Methodology for Assessing High Strain Rate Mechanical Response of Soft Biomaterials

A Coupled Experiment-finite Element Modeling Methodology for Assessing High Strain Rate Mechanical Response of Soft Biomaterials

Published on: May 18, 2015

Area of Science:

Biomechanics
Materials Science
Biomedical Engineering

Background:

Accurate material models for soft tissues, especially brain tissue, are crucial for computational biomechanics.
Most research focuses on shear loading, leaving compression behavior less understood.

Purpose of the Study:

To develop and validate a viscoelastic constitutive model for bovine brain tissue under uniaxial compression.
To investigate the applicability of quasi-linear viscoelasticity (QLV) and specific hyperelastic models for brain tissue.

Main Methods:

A viscoelastic constitutive model was developed for finite step-and-hold uniaxial compression (10 s⁻¹ ramp, 20 s hold).
Quasi-linear viscoelasticity (QLV) assumption was validated up to 35% strain.
Generalized Rivlin and two-parameter Ogden models were used for isochoric and volumetric deformation, respectively.
Hyperelastic parameters were fitted to isochronous curves (0.06 s and 14 s).

Main Results:

The QLV assumption was valid for strains up to 35%.
At least three terms (C(10), C(01), C(11)) of the generalized Rivlin model were necessary for accurate isochoric deformation.
The two-parameter Ogden model provided insights into the material's incompressibility.
Viscoelastic relaxation was characterized across various decay rates, with comparisons to existing models in compression and tension.

Conclusions:

The developed viscoelastic model accurately captures the behavior of bovine brain tissue under uniaxial compression.
The study highlights the importance of specific constitutive models and parameters for simulating soft tissue mechanics.
Findings contribute to improved computational models for brain injury and surgical simulations.