On The Validity Extent Of Linear Viscoelastic Models Of Human Brain

Characterization of human brain material properties in the form of computationally feasible mathematical models is a complex problem; especially when the models are used in complicated Finite Element simulations. Various models have been proposed to include the tissue’s hyper-viscoelasticity, most of which are quite complicated and therefore only suited to Software-based Finite Element methods. Use of linear material models simplifies the problem and saves much time and effort, allowing the researcher to verify the results of more sophisticated models with lower computational cost. However, the preciseness of the results from such models is subject to special conditions. This study proposes and validates a Generalized Maxwell linear viscoelastic model with five constants to be used as an acceptable computational method to simulate brain’s viscoelastic behavior at low strain rates. To this end, an explicit numerical integration scheme is used to simulate the single-DOF tissue response with a Generalized Maxwell viscoelastic model. Using the material constants of a previous hyper-viscoelastic model, the results are compared with those obtained from a previous experiment. The comparison shows that the linear GM viscoelastic model is predicting the low-strain-rate behavior of the brain tissue with acceptable error.