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Published on: October 20, 2023
Parameter estimation by descent and genetic algorithm methods of an in-vitro stenosis bypass model
1Department of Electrical and Computer Engineering, The University of Texas at El Paso, El Paso, TX 79968, USA.
Summary
Improved hemodynamic impedance models help understand arterial disease. This study used advanced manufacturing for in-vitro experiments to create these models, aiding in the study of arterial stenosis.
Area of Science:
- Biomedical Engineering
- Fluid Dynamics
- Medical Device Technology
Background:
- Arterial diseases like stenosis pose significant health risks.
- Accurate hemodynamic models are crucial for understanding disease progression and treatment.
- Current modeling techniques may not fully capture complex arterial hemodynamics.
Purpose of the Study:
- To develop improved lumped-parameter hemodynamic impedance models for arterial stenosis.
- To utilize advanced manufacturing for creating physiologically relevant in-vitro models.
- To estimate flow-to-pressure transfer functions for enhanced hemodynamic analysis.
Main Methods:
- In-vitro experimentation with advanced manufacturing techniques.
- Utilizing physiologically relevant geometries and flow conditions simulating arterial stenosis.
- Applying conventional descent and Genetic Algorithm methods to estimate transfer functions.
Main Results:
- Successful estimation of flow-to-pressure transfer functions.
- Development of a lumped-parameter impedance model for the arterial system.
- Generated data suitable for further hemodynamic studies of stenosis.
Conclusions:
- The developed hemodynamic impedance models provide a valuable tool for studying arterial stenosis.
- Advanced manufacturing enables realistic in-vitro testing for hemodynamic research.
- This approach facilitates a deeper understanding of hemodynamics in diseased arteries.
