Improving regulation of mean arterial blood pressure during anesthesia through estimates of surgery effects

In this paper, a scheme for improvement of the regulation of mean arterial blood pressure (MAP) during anesthesia based on model predictive control (MPC) and estimates of the effects of disturbances (surgical events) is proposed. A linear model for the combined effects of surgical stimulations and volatile anesthetics on MAP is derived from experimental data. Based on it the potential improvement in blood pressure regulation is evaluated via a simulation study. The simulation study shows that when information about the effect of the surgical events on MAP is utilized by the controller maximum MAP deviations can be reduced by as much as 50% even when this information is inaccurate. At worst, (highly inaccurate information) no improvement is obtained.