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Identifiability of tissue material parameters from uniaxial tests using multi-start optimization
Babak N Safa1, Michael H Santare2, C Ross Ethier3
1Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology/Emory University, Atlanta, GA, USA; Department of Biomedical Engineering, University of Delaware, Newark, DE, USA; Department of Mechanical Engineering, University of Delaware, Newark, DE, USA.
This study introduces a method to assess the identifiability of material parameters in soft tissue biomechanics. It reveals that not all parameters are uniquely determined by standard mechanical tests, impacting model validity.
Area of Science:
- Biomechanics
- Materials Science
- Biomaterials Engineering
Background:
- Determining tissue biomechanical properties is crucial for various applications.
- The identifiability of constitutive model parameters in tissue mechanics is a significant challenge.
- Existing curve-fitting methods lack a framework for studying parameter identifiability.
Purpose of the Study:
- To assess material parameter identifiability for constitutive models of fiber-reinforced soft tissues.
- To establish a generalizable procedure for studying parameter identifiability in biomechanics.
- To investigate the impact of including lateral strain on parameter identifiability.
Main Methods:
- Generated synthetic data simulating uniaxial tension and compression tests.
- Employed a multi-start nonlinear least-squares optimization technique with multiple initial parameter guesses.
- Utilized constitutive models for fiber-reinforced tissues, exemplified by tendon and sclera.
Main Results:
- Not all constitutive model parameters were identifiable from uniaxial mechanical tests alone, despite achieving good fits to stress-stretch data.
- Incorporating lateral strain as an additional fitting criterion improved parameter identifiability but did not identify all parameters.
- Demonstrated that parameter identifiability is a critical consideration in constitutive modeling of soft tissues.
Conclusions:
- A practical framework for assessing parameter identifiability in tissue mechanics was established.
- Uniaxial mechanical tests alone are insufficient for uniquely determining all parameters in complex soft tissue models.
- Further research is needed to develop robust methods for parameter identifiability in biomechanical modeling.
