A Modular Patient Simulator for Evaluation of Decision Support Algorithms in Mechanically Ventilated Patients

Abstract

Mechanical ventilation is a life-saving intervention, which, despite being routinely used in ICUs, poses the risk of causing further damage to the lung tissue if the ventilator is set inappropriately. Medical decision support systems may help in optimizing ventilator settings according to therapy goals given by the clinician. Before using the decision support algorithms in commercially available systems, extensive tests are necessary to ensure patient safety and correct decision making. Model-based patient simulators can assist in evaluating such decision support systems by creating different clinical scenarios. We propose a new Java based patient simulator that implements various models of respiratory mechanics, gas exchange and cardiovascular dynamics to form a complex patient model. The implemented models interact with one another to allow simulation of the ventilators influence on various physiological processes. Model simulations are running in real-time and simulation results can be extracted via multiple interfaces. Each of the implemented models has been validated to exhibit physiologically correct behavior. Results of the combined model system also showed to be physiologically plausible.