Key result
Delta operator method successfully identifies physiological parameters online during preclinical left ventricular assist system support.
A new method using the delta operator and a second-order systemic circulation model can efficiently identify physiological parameters online to support medical care with artificial hearts.
Animal data support online LVAD parameter identification feasibility; leaves open human translation and validation.
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.
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Kosaka et al. (2002) studied Artificial heart / left ventricular assist system. Online parameter identification using the delta operator was evaluated on Identification of physiological parameters (Ra, Ca, L, Rp). A new method using the delta operator successfully identified physiological parameters online during an animal experiment with a left ventricular assist system.
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