Hemodynamic regulation using fuzzy logic

Abstract

Abstract-After cardiac surgery patients often show a cardiovascular instability, which has to be managed by infusing different vasoactive drugs. This work proposes a closed-loop system to automatically react upon changes in the patients state and trigger infusion of indicated drugs. As input signals mean arterial pressure, cardiac output, central venous pressure and systemic vascular resistance were chosen. The vasoactive drugs used are isosorbide dinitrate, norepinephrine, dopamine and additionally hydroxyethyl starch. The controller itself is designed as a controller system with four internal fuzzy controllers, one for each medication dosage to be calculated. The proposed controller is tested with a simulation environment. The environment is able to simulate a canine cardiovascular system and reactions to different medications. The controller is evaluated for three different diseases, for congestive heart failure, hypotension and hypertension. The fuzzy controller system is able to react adequately in all these test cases in the simulation and regulates the hemodynamic signals back within a range of the desired target values.

Evaluation of an adaptive algorithm for fuzzy type-2 control in blood pressure regulation

“…The initial controller was based on fuzzy logic [2]. The four inputs were mean arterial pressure (MAP), cardiac output (CO), systemic vascular resistance (SVR) and central venouse pressure (CVP).…”

“…Figure 4 shows the resulting lower and upper membership functions for MAP exemplary. Enhanced Interval Approach (EIA), individual sets of different physicians depicted in colours, the black outline represents the resulting EIA lower and upper membership function as implemented by [8] [9] Using the data from the questionnaire and the EIA all input and output T2 membership functions were defined to replace the initial T1 fuzzy sets defined by only one physician [2]. The type reduction in the EIA T2 Controllers is done via the centre of sets method.…”

“…According to Bates [1] this is one of the main reasons why it is so suitable for medical decision making. In previous research publications a fuzzy controller was described for automated blood pressure regulation with drugs [2] [3]. In this case one single physician was asked to define membership functions and rules for that purpose.…”

Learning a fuzzy system from training data using the Münsteraner Optimisation System

“…The advantage here is, that a person, even without knowledge about fuzzy theory can understand how such a fuzzy rule works. That is why our research group is working on a fuzzy controller to automate blood pressure regulation for intensive care patients [1]. Currently we are collecting data from the intensive care unit to analyze the medical doctor's behaviour in regulating the blood pressure manually by changing dosages of certain drugs.…”

System design for simultaneous data acquisition from patient monitor and syringe pumps in intensive care unit

“…In our own department at the German Heart Centre we have been researching e.g. on automated hemodynamic regulation with drugs [1] or the automation of a heart-lung machine [2]. Other research groups have been working on automatic anesthesia [3] or even beds, which can turn comatose patients automatically [4] for example.…”