Dynamic mechanical characterization and viscoelastic modeling of bovine brain tissue

Brain tissue is vulnerable and sensitive, predisposed to potential damage under various conditions of mechanical loading. Although its material properties have been investigated extensively, the frequency-dependent viscoelastic characterization currently limited. Computational models can provide a non-invasive method by which analyze brain injuries predict response tissue. The are expected be induced dynamic loading, mostly in compression measurement essential improve accuracy variety finite element simulations on Thus, aim this study was investigate compressive present mathematical model frequency domain capture behavior based experimental results. Bovine specimens, obtained from four locations corona radiata, corpus callosum, basal ganglia cortex, were tested using analysis over range frequencies between 0.5 35 Hz characterize regional directional bovine heterogenous for regions but not sensitive orientation showing dependent statistical results, with increasing frequency. mean storage loss modulus found 12.41 kPa 5.54 kPa, respectively. parameters linear numeric simulation across frequencies. will fidelity computational head information prediction clinical treatments.