Other Models

In addition to the models of Section 2, other lumped parameter models of the pulsatile heart and circulation and resting physiologic perturbation models may be implemented with the RCVSIM source code. These models may only be implemented at the MATLAB prompt by executing simulate.mexlx. A brief description of each of these models and the relevant MATLAB functions is given below.

• Lumped parameter models of the pulsatile heart and circulation
  • Left ventricle preparation. The electrical circuit analog of this preparation may be visualized by replacing $C_a$ and $C_{pv}$ in Figure 1 with the DC voltage sources $P_a$ and $P_{pv}$, respectively. This preparation may be utilized for the analysis of the input-output properties of the left ventricle model; however, there is currently no source code to alter the DC voltage sources during a single simulation. The initial pressure, volume, and flow rate of the preparation are computed with the function lv_init_cond.m, and the derivative of the pressure at a desired time step is determined with the function lv_eval_deriv.m.
  • Intact circulatory preparation for measurement of single ventricular contraction $P_a(t)$ response. The electrical circuit analog of this preparation is given by Figure 1and includes an additional parameter ($nve$) which represents the beat number after which the ventricles will no longer contract. The single ventricular contraction $P_a(t)$ response may then be determined by executing the preparation for $nve$, and then $nve$-1, ventricular contractions and then taking the difference between the two resulting $P_a(t)$ waveforms.
  • Intact circulatory preparation with only linear elements. The electrical circuit analog of this preparation is given by Figure 1 in which the four nonlinear elements are replaced by purely linear elements. This model was previously presented by Davis [3]. The initial pressures, volumes, and flow rates of the preparation are computed with the function init_cond.m, and the derivative of the pressures at a desired time step is determined with the function eval_deriv.m.
  • Intact circulatory preparation with third-order systemic arteries. The electrical circuit analog of this preparation may be visualized by replacing the capacitor $C_a$ in Figure 1 with two grounded capacitors connected via an inductor. The capacitor proximal to the left ventricle compartment represents the large, elastic ($e$) arteries, the other capacitor represents the small, muscular ($m$) arteries, and the inductor ($L_e$) accounts for the inertial effects of blood flow between the two lumped arteries. This third-order model of the systemic arteries was previously presented by Clark [2]. The $P_m(t)$ waveform may be considered as a first-order approximation of a peripheral arterial blood pressure waveform. The initial pressures, volumes, and flow rates of the preparation are computed with the function third_init_cond.m, and the derivative of the pressures at a desired time step is determined with the function third_eval_deriv.m.
  • Intact circulatory preparation with nonlinear systemic arterial compliance. The electrical circuit analog of this preparation is given by Figure 1 with a box encompassing $C_a$ to denote its nonlinearity. This nonlinear element is characterized by the curvature ($K$), differential compliance ($C_a$), and volume ($Q_{nac}$) all at $P_a^{sp}$. Provided that $K<0$, the differential compliance decreases with increasing $P_a(t)$. The initial pressures, volumes, and flow rates of the preparation are computed with the function nac_init_cond.m, and the derivative of the pressures at a desired time step is determined with the function nac_eval_deriv.m.
  • Intact circulatory preparation with third-order systemic arteries and nonlinear, large elastic arterial compliance. This preparation is a combination of the previous two preparations with a nonlinear $C_e$ and linear $C_m$. The initial pressured, volumes, and flow rates of the preparation are computed with the function third_nac_init_cond.m, and the derivative of the pressures at a desired time step is determined with the function third_nac_eval_deriv.m.
  • Intact circulatory preparation with an arterial pressure reservoir preparation. The electrical circuit analog of this preparation may be visualized by replacing $C_a$ in Figure 1 with a DC voltage source $P_a$. This preparation may be utilized to understand hemodynamics while $P_a(t)$ is held constant. The initial pressures, volumes, and flow rates of the preparation are computed with the function apr_init_cond.m, and the derivative of the pressures at a desired time step is determined with the function apr_eval_deriv.m.
  • Intact circulatory preparation with contracting atria. The electrical circuit analog of this preparation may be visualized by inserting right atrial ($ra$) and left atrial ($la$) compartments (linear resistor and linear, variable capacitor with an unstressed volume) between the venous and ventricular compartments in Figure 1. The atrial and ventricular compliances at a desired time step are respectively computed by the functions var_vcap.m and var_acap.m. The initial pressures, volumes, and flow rates of the preparation are computed with the function a_init_cond.m, and the derivative of the pressures at a desired time step is determined with the function a_eval_deriv.m.
• Resting physiologic perturbations
  • Respiratory activity. In addition to fixed-rate breathing and random-interval breathing with varying tidal volumes, $Q_{lu}(t)$ may also be represented as a step or impulse of desired amplitude or area (Qfrs) and at a desired time (Qfrt) as well as at random-intervals with a constant tidal volume. These breathing patterns are generated with the function resp_act.m.
  • Autoregulation of local vascular beds. In addition to bandlimited white noise, autoregulation of local vascular beds may also be represented as bandlimited, 1/f noise or a sinusoid of desired amplitude (ar) and frequency (fr). The former representation is generated with the functions bl_filt.m and oneoverf_filt.m.
  • Central oscillator. A central oscillator is represented as an exogenous, sinusoidal disturbance to $P_a^{sp}$ of desired amplitude (ap) and frequency (fp).
  • Non-baroreflex mediated fluctuations in $Q_v^0(t)$. Fluctuations in $Q_v^0(t)$ not due to the baroreflexes are represented as a white disturbance of desired standard deviation (stdwq) that is bandlimited to a desired frequency ($fcoq$). These fluctuations may specifically be due to, for example, fast acting hormonal loops. These fluctuations are generated with the function bl_filt.m.

In order to implement all of the above models, rather than using read_param.m, the parameter vector th must be created by first copying the file $DIR/bin/header_def.m to the current directory and then executing th=header_def; at the MATLAB prompt (Note that header_def.m can be copied to any name as long as it has the extension .m). Additionally, the appropriate option of the arguments to simulate.mexlx (type help simulate at the MATLAB prompt) must be selected.