Session:

Mini-Symposia: Computational Medicine Building and Applying Intelligent Systems in Health
Tuesday, March 02, 2004, 17.35-17.55

Session Chair:

Peter Kokol

Paper Title:

A Hybrid Model-Based ReasoningVentilatory Decision Support System

Author(s):

Dr. D. Linkens, University of Sheffield, Sheffield, U.K.
H.F.Kwok, University of Sheffield, Sheffield, U.K.
M.Mahfouf, University of Sheffield, Sheffield, U.K.
G.H.Mills, University of Sheffield, Sheffield, U.K.

Abstract:

A hybrid knowledge-and-model-based advisory system for intensive care ventilator management has been developed. The system consists of two parts: a knowledge-based top-level module using neural fuzzy technology and a model-based lower-level module consisting of 4 sub-units. The system generates advice on four ventilator settings (the inspired fraction of oxygen (FiO2), positive end-expiratory pressure (PEEP), peak inspiratory pressure (PINSP) and ventilatory rate) based on the patient's routine and cardio-respiratory measurements. The top-level module and the sub-units of the lower level module are implemented in MATLAB scripts and SIMULINK.LABVIEW provides the graphics user interface and the flow control of the program.The validation results of the top-level module are encouraging. Validation of the integrated system using retrospective clinical data is underway.A good PEEP model will be required for future develpoment of the PEEP control sub-unit of the lower level module.