Fig 1.
The framework of the on-line parameter identification.
Fig 2.
The complete cardiovascular system model used for validating the identification algorithm.
Fig 3.
The five-element lumped model of the arterial system.
pao, aortic pressure; Qao, aortic flowrate; psv, systemic venous pressure; Rsa,0, characteristic systemic resistance; Rsa, systemic arterial resistance; Lsa, systemic arterial inertance; Csa,1 and Csa,2, two components of the arterial compliance; and
, flowrates through the two compliances; psa, pressure before pressure drop of the systemic arterial resistance.
Table 1.
Maximum and minimum physiological values of the parameters.
Fig 4.
Simulated pressure and flow waveforms from the complete numerical cardiovascular model under the normal condition: (a) left ventricular pressure, aortic pressure and venous pressure, (b) aortic flow rate.
Fig 5.
Simulated Pressure and flow waveforms during the variation of parameter values: (a) aortic pressure and venous pressure, (b) aortic flow rate.
Fig 6.
Plots of the on-line identified results of the five parameters.
(a) Rsa and Csa,1, (b) Rsa,0 and Csa,2, (c) Lsa.
Table 2.
Mean and standard deviation for the values of the on-line identified five parameters in the normal condition simulation.
Fig 7.
The predicted output of the lumped arterial model with identified parameter values and the simulated data from the numerical cardiovascular model.
Fig 8.
The parameter identification time for every cardiac cycle during simulation.
Fig 9.
Bode plot of the parameter sensitivities of the model near the normal values in Table 1.
Sensitivity to the parameters (a) Rsa,0; (b) Rsa; (c) Csa,1; (d) Csa,2; (e) Lsa.