Fuzzy Logic based Identification of Operator Functional States Using Multiple Physiological and Performance Measures

Abstract

This paper assesses the operator functional state (OFS) based on a collection of psychophysiological and performance measures. Two types of adaptive fuzzy models, namely ANFIS (adaptive-network-based fuzzy inference system) and GA (genetic algorithm) based Mamdani fuzzy model, are employed to estimate the OFSs under a set of simulated process control tasks involved in an automation-enhanced cabin air management system (aCAMS). The adaptive fuzzy modelling procedures are described and then validated using real-life data measured from such a simulated human-machine process control system.