Multiple-drug hemodynamic control using fuzzy decision theory

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Abstract
A fuzzy-logic-based, automated drug-delivery system has been developed and validated on a nonlinear canine circulatory model for managing hemodynamic states. This controller features: 1) a fuzzy decision analysis module for patient status determination by assessing cardiac index, systemic vascular resistance index, and pulmonary vascular resistance index and 2) a fuzzy hemodynamic management module utilizing dopamine, phenylephrine, nitroprusside, and nitroglycerin for regulating mean arterial pressure, mean pulmonary arterial pressure, and cardiac output. A rule-based drug delivery scheduling program has been devised and incorporated to execute the therapeutic strategy as recommended by the decision analysis module. Compared to the existing controllers, this system is able to achieve a faster response time with a more secured and effective regulation. The simulation results have demonstrated the feasibility of the decision analysis process for automated management of the arterial and venous circulation with an expanded arsenal of pharmacological agents.