Digital twin for the formal analysis of a depth of anesthesia controller

Abstract

Effective management of depth of anesthesia (DoA) is crucial for patient safety in healthcare. Anesthesiologists typically adjust anesthetic dosages to maintain desired sedation, analgesia (pain relief), and muscle relaxation states. In this paper, we present a digital twin (DT) architecture for the formal modeling and verification of an infusion pump controller for DoA management. The DT incorporates a virtual patient model, an autonomous DoA controller adjusting the infusion rate of the anesthetic agent, i.e., propofol, a test-case manager, and a runtime verification monitor. Data exchange occurs via Ethernet frames. Challenges arise from noise in the Bispectral Index monitoring system readings and infusion rate measurements in clinical scenarios. To mitigate noise impact, we design a feedback controller that is robust against noise. We reason about DT performance by evaluating control specifications using a temporal-logic language within the context of our runtime verification tool.