  In this paper, we present an approach for modeling bio-tissues that
incorporates the variability in properties as part of their characteristics.
This is achieved by considering the parameters of the model of a biomaterial to
themselves be random variables and represented by a probability distribution
over the space of parameters. This probability distribution is obtained by the
systematic use of Bayesian inference together with a continuum mechanics based
solution of a boundary value problem. We illustrate this approach by
characterizing sheep arteries by using a combination of experimental data and
different hyperelastic models. Furthermore, we also develop a model based
Bayesian classification of new data into different classes based on the
computed model parameter probability distribution.
