Anesthesia infusion models: knowledge-based real-time identification via stochastic approximation

The modeling and identification methodology introduced in the paper captures the unique features encountered in developing a computer-aided control strategy for anesthesia drug infusion. Rather than using models of high complexity, we follow the insights of anesthesiologists in representing the basic features of a patient response to drug infusion that are essential for computer-aided infusion control. The model parameters are initiated by expert knowledge and improved upon in real-time when clinical measurement data become available.