On parameter estimation for biaxial mechanical behavior of arteries

Shahrokh Zeinali-Davarani, Jongeun Choi, Seungik Baek

Research output: Contribution to journalArticlepeer-review

43 Citations (Scopus)

Abstract

This article considers the parameter estimation of multi-fiber family models for biaxial mechanical behavior of passive arteries in the presence of the measurement errors. First, the uncertainty propagation due to the errors in variables has been carefully characterized using the constitutive model. Then, the parameter estimation of the artery model has been formulated into nonlinear least squares optimization with an appropriately chosen weight from the uncertainty model. The proposed technique is evaluated using multiple sets of synthesized data with fictitious measurement noises. The results of the estimation are compared with those of the conventional nonlinear least squares optimization without a proper weight factor. The proposed method significantly improves the quality of parameter estimation as the amplitude of the errors in variables becomes larger. We also investigate model selection criteria to decide the optimal number of fiber families in the multi-fiber family model with respect to the experimental data balancing between variance and bias errors.

Original languageEnglish
Pages (from-to)524-530
Number of pages7
JournalJournal of Biomechanics
Volume42
Issue number4
DOIs
Publication statusPublished - 2009 Mar 11

Bibliographical note

Funding Information:
This work was supported by IRGP grant from Michigan State University. The authors thank Professor J.D. Humphrey at Texas A&M University for valuable discussions.

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Orthopedics and Sports Medicine
  • Biomedical Engineering
  • Rehabilitation

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