An expert system for interpreting ICU monitor data

Abstract

By performing analysis, we propose and describe an expert system called ASSOCIATE which analyses the historical voluminous high frequency and noisy data generated by the monitors of an Intensive Care Unit (ICU) for the purposes of summarisation and patient state assessment. ASSOCIATE is an associational reasoner and consists of 4 sub-systems: data filtering which is used to remove noise; interval identification to generate trends (intervals of time where the data is either increasing, decreasing or steady) from the filtered data; interpretation which performs summarisation and patient state assessment by applying rules from a knowledge base sub system to overlapping trends to identify clinically significant events. © 2011 Springer-Verlag Berlin Heidelberg.