Robust predictive control strategy applied for propofol dosing using BIS as a controlled variable during anesthesia.

Area of Science:

• Anesthesiology
• Control Engineering
• Biomedical Engineering

Background:

• Anesthesia drug dosing requires precise control to maintain patient safety and surgical conditions.
• Existing anesthesia-specific control algorithms face challenges with patient variability.
• Predictive control offers a potential solution for adaptive and robust drug delivery.

Purpose of the Study:

• To evaluate a generic predictive control strategy for propofol drug dosing during anesthesia.
• To assess the robustness of the predictive controller against inter- and intrapatient variability.
• To determine the controller's stability and applicability in simulated surgical environments.

Main Methods:

• A single-input (propofol) single-output (bispectral index, BIS) patient model was used for prediction and simulation.
• A generic predictive control strategy was applied and compared with an anesthesia-specific algorithm.
• Robustness was evaluated using 12 different patient models, incorporating interpatient variability and disturbances.

Main Results:

• The predictive controller demonstrated robust performance across diverse patient models and simulated disturbances.
• The controller maintained stability within a predefined range, ensuring predictable drug dosing.
• Simulation studies indicated the predictive controller's suitability for real-life anesthesia drug administration.

Conclusions:

• Generic predictive control is a robust and stable method for anesthesia drug dosing.
• The controller effectively manages inter- and intrapatient variability, enhancing patient safety.
• Simulation results support the clinical applicability of this predictive control strategy in anesthesia.