Stress relaxation and recovery in tendon and ligament: experiment and modeling.

Accurate joint models require the ability to predict soft tissue behavior. This study evaluates the ability of constitutive equations to predict the nonlinear and viscoelastic behavior of tendon and ligament during stress relaxation testing in a porcine model. Three constitutive equations are compared in their ability to model relaxation, recovery and reloading of tissues. Quasi-linear viscoelasticity (QLV) can fit a single stress relaxation curve, but fails to account for the strain-dependence in relaxation. Nonlinear superposition can fit the single relaxation curve and will account for the strain-dependent relaxation behavior, but fails to accurately predict recovery behavior. Schapery's nonlinear viscoelastic model successfully fits a single relaxation curve, accounts for strain-dependent relaxation behavior, and accurately predicts recovery and reloading behavior. Comparing Schapery's model to QLV and nonlinear superposition, Schapery's method was uniquely capable of fitting the different nonlinearities that arise in stress relaxation curves from different tissues, e.g. the porcine digital flexor tendon and the porcine medial collateral ligament (MCL), as well as predicting subsequent recovery and relaxation curves after initial loads.