Assessing Control Performance in Closed-loop Anesthesia

Recently, several control systems for closed-loop anesthesia have been demonstrated both in simulation and clinical studies. A set of performance measures, proposed by Varvel et al., have constituted the standard means of comparing such systems. This paper debates the adequacy of the Varvel measures, as applied to closed-loop anesthesia, and proposes an alternative set of measures. Key features of the proposed measures are: wide acceptance within the control community; reflection of clinical feasibility; separate measures for induction and maintenance of anesthesia; separation of outlier detection and performance evaluation. The proposed measures are descriptive, few, and easy to compute

A Synthesis Method for Automatic Handling of Inter-patient Variability in Closed-loop Anesthesia

This paper presents a convex-optimization-based technique to obtain parameters for a PID feedback controller, used to control the infusion rate of the anesthetic drug propofol. The controller design is based on a set of identified patient models, relating propofol infusion to an EEG-based conciousness index. The main contribution lies in the method automatically taking inter-patient variability into account, i.e., it guarantees robustness (sensitivity peak) and performance (disturbance rejection) over a set of patient models, without the need for manual intervention. The method is demonstrated using a clinically relevant design example. A controller designed using the proposed method is currently scheduled for clinical evaluation

Coordinated semi-adaptive closed-loop control for infusion of two interacting medications

This paper presents a coordinated and semi‐adaptive closed‐loop control approach to the infusion of 2 interacting medications. The proposed approach consists of an upper‐level coordination controller and a lower‐level semi‐adaptive controller. The coordination controller recursively adjusts the reference targets based on the estimated dose‐response relationship of a patient to ensure that they can be achieved by the patient. The semi‐adaptive controller drives the patient outputs to the reference targets while estimating the patient's dose‐response relationship online. In this way, the controller is resilient to unachievable caregiver‐specified reference targets and responsive to the medication needs of individual patients. To establish the proposed approach, we developed the following: (1) a linear two‐input–two‐output dose‐response model; (2) a two‐input–two‐output semi‐adaptive controller to regulate the patient outputs while adapting high‐sensitivity parameters in the patient model; and (3) a coordination controller to adjust the reference targets that reconcile caregiver inputs and medication use. The proposed approach was applied to an example scenario in which cardiac output and respiratory rate are regulated via infusion of propofol and remifentanil in an in silico simulation setting. The results show that the coordinated semi‐adaptive control could (1) track achievable reference targets with consistent transient and steady‐state performance and (2) resiliently adjust the unachievable reference targets to achievable ones