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

Authors:
Jian-Hua Zhang;Xing-Yu Wang;M. Mahfouf;D. A. Linkens
Affiliations:
-;-;-;-
Venue:
BMEI '08 Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01
Year:
2008

Citing 0
Cited 1

Operator functional state classification using least-square support vector machine based recursive feature elimination technique

Computer Methods and Programs in Biomedicine

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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.