Online parameter identification of second-order systemic circulation model using the delta operator

To develop effective medical care with the artificial heart, we proposed a new method that can calculate the time varying and unmeasured hemodynamics of the human body from measured physiological data: aortic pressure, aortic flow, and pump flow in real time. This method comprises first, the second order of systemic circulation model, which consists of aortic compliance (Ca), aortic resistance (Ra), aortic inertia (L), and total peripheral resistance (Rp); and second, system identification using the delta operator. In the computer simulation, we confirmed the effectiveness of this method. During the animal experiment with the left ventricular assist system, the physiological parameters could be identified online: mean Ra = 0.04 mm Hg s/ml, mean Ca = 0.65 mm Hg/ml, mean L = 0.004 mm Hg s(2)/ml, and mean Rp = 0.3 mm Hg s/ml. This new method efficiently identified the physiological parameters, which are important not only to support the medical care but also to develop the control method adapted to the physiological behavior.