ACLAC: An approach for adaptive closed-loop anesthesia control

Abstract

In current practice, to control the anesthetic process, the anesthetist delivers drugs according to the surgery procedure and to the current patient characteristics and state. This is an open-loop procedure requiring an active participation of the medical expert. We propose an adaptive closed-loop controller for the regulation of hypnosis for patients undergoing general anesthesia. One of the main problems arising when designing such a controller is related to the intra- and inter-patient variability. We employ a simple regression model to make prediction of patient's response and to compute the adequate doses of propofol to keep the patient in the specified Bispectral Index target. To make our model adaptive, we continuously monitor the patient behavior and detect changes in patient response to update the identification model. Experimental evaluation on real patients data shows that we can effectively detect change points. Simulation of the adaptive closed-loop control with the change detection mechanism also suggests that the use of the adaptation mechanism improves the control.