On-line parameter identification of the lumped arterial system model: A simulation study.

Area of Science:

• Biomedical Engineering
• Cardiovascular Physiology
• Computational Modeling

Background:

• Lumped models of the arterial system are used in hybrid mock loops for real-time response.
• Current models use general parameters, lacking patient-specific adaptation.

Purpose of the Study:

• To develop an on-line parameter identification method for a five-element lumped arterial model tailored to individual patients.
• To enable customized hybrid mock loops and real-time clinical monitoring of arterial characteristics.

Main Methods:

• Utilized a five-element lumped arterial model with aortic flow rate and venous pressure as inputs, and aortic pressure as output.
• Employed iterative optimization based on state-space equations to minimize prediction error for parameter identification.
• Validated the method using simulated data from a comprehensive numerical cardiovascular model.

Main Results:

• The developed method accurately tracked dynamic variations in model parameters.
• Sensitivity analysis provided insights into the impact of parameter changes on the model.
• The identification performance demonstrated the method's effectiveness.

Conclusions:

• The on-line parameter identification method shows significant potential for customizing hybrid mock loops for specific patients.
• This approach can facilitate real-time clinical monitoring of arterial vessel characteristics.
• The study highlights the feasibility of personalized cardiovascular modeling.