An optimal parameter estimation method for soft tissue characterization

Abstract

This paper presents a gradient-free direct search estimation method by using genetic algorithm to model and predict the elastic stress response of ligament based on quasi-linear viscoelastic (QLV) theory. An improved genetic algorithm is developed to simultaneously fit the ramping and relaxation experimental data to the QLV constitutive equation for obtaining soft tissue parameters in a time-saving process. Experiments and comparison analysis with the existing methods for two exponential and polynomial QLV models are conducted, demonstrating that the proposed method can accurately estimate soft tissue parameters and satisfy the time-saving requirement of intraoperative soft tissue characterization.

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“…Genetic algorithms have been used in similar situations to estimate the parameters in equations modelling different phenomena. For example, similar algorithms have been used on biomechanical models of soft tissues [18], distribution fitting [19], electrostatic discharge models [20], atmospheric temperature profiles [21], and PID (proportional-integralderivative) controller optimisation [16].…”