Parameter estimation using the quasi-linear viscoelastic model proposed by Fung.

Area of Science:

• Biomedical Engineering
• Materials Science
• Biomechanics

Background:

• Soft biological tissues exhibit viscoelastic properties, crucial for understanding their mechanical behavior.
• Fung's quasi-linear viscoelastic model is widely used to describe this time-dependent behavior.
• Parameter estimation typically relies on relaxation experiments, often using approximated step-strain inputs.

Purpose of the Study:

• To investigate discrepancies in parameter estimation for Fung's quasi-linear viscoelastic model.
• To identify which parameters are most affected by the practical limitations of step-strain application.
• To propose improved methods for estimating the fast viscous parameter (tau 1).

Main Methods:

• Utilized a hypothetical quasi-linear viscoelastic material for analysis.
• Simulated relaxation experiments with idealized and practical (steplike) strain changes.
• Analyzed the impact of strain input approximation on parameter estimation accuracy.

Main Results:

• Significant discrepancies were observed between exact and estimated parameter values.
• The parameter tau 1, governing fast viscous phenomena, showed the largest estimation errors.
• The study identified specific conditions leading to these inaccuracies.

Conclusions:

• Practical limitations in applying step-strain inputs introduce notable errors in viscoelastic parameter estimation.
• Accurate estimation of the fast viscous parameter (tau 1) is challenging but critical.
• Methods for improving tau 1 estimation in specific scenarios are presented.