Parameter Identification Methods in a Model of the Cardiovascular System

Type of content
Conference Contributions - Published
Publisher's DOI/URI
Thesis discipline
Degree name
Publisher
University of Canterbury. Mechanical Engineering
Journal Title
Journal ISSN
Volume Title
Language
Date
2015
Authors
Pironet, A.
Desaive, T.
Dauby, P.C.
Chase, Geoff
Docherty, P.D.
Abstract

To be clinically relevant, mathematical models have to be patient-specific, meaning that their parameters have to be identified from patient data. To achieve real time monitoring, it is important to select the best parameter identification method, in terms of speed, efficiency and reliability. This work presents a comparison of seven parameter identification methods applied to a lumped-parameter cardiovascular system model. The seven methods are tested using in silico and experimental reference data. To do so, precise formulae for initial parameter values first had to be developed. The test results indicate that the trust-region reflective method seems to be the best method for the present model. This method (and the proportional method) are able to perform parameter identification in two to three minutes, and will thus benefit cardiac and vascular monitoring applications

Description
Citation
Pironet, A., Desaive, T., Dauby, P.C., Chase, J.G., Docherty, P.D. (2015) Parameter Identification Methods in a Model of the Cardiovascular System. Berlin, Germany: 9th IFAC Symposium on Biological and Medical Systems (BMS 2015), 31 Aug-2 Sep 2015.
Keywords
parameter identification, mathematical models, biomedical systems, medical applications
Ngā upoko tukutuku/Māori subject headings
ANZSRC fields of research
Fields of Research::40 - Engineering::4003 - Biomedical engineering::400303 - Biomechanical engineering
Field of Research::11 - Medical and Health Sciences::1102 - Cardiovascular Medicine and Haematology
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