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2008 International Conference on BioMedical Engineering and Informatics
Fuzzy Logic based Identification of Operator Functional States Using Multiple Physiological and Performance Measures
May 27-May 30
ISBN: 978-0-7695-3118-2
ASCII Text
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Jian-Hua Zhang, Xing-Yu Wang, M. Mahfouf, D.A. Linkens, "Fuzzy Logic based Identification of Operator Functional States Using Multiple Physiological and Performance Measures," BioMedical Engineering and Informatics, International Conference on, vol. 1, pp. 570-574, 2008 International Conference on BioMedical Engineering and Informatics, 2008.
 
 
BibTex
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@article{ 10.1109/BMEI.2008.181,
author = {Jian-Hua Zhang and Xing-Yu Wang and M. Mahfouf and D.A. Linkens},
title = {Fuzzy Logic based Identification of Operator Functional States Using Multiple Physiological and Performance Measures},
journal ={BioMedical Engineering and Informatics, International Conference on},
volume = {1},
year = {2008},
isbn = {978-0-7695-3118-2},
pages = {570-574},
doi = {http://doi.ieeecomputersociety.org/10.1109/BMEI.2008.181},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - BioMedical Engineering and Informatics, International Conference on
TI - Fuzzy Logic based Identification of Operator Functional States Using Multiple Physiological and Performance Measures
SN - 978-0-7695-3118-2
SP570
EP574
A1 - Jian-Hua Zhang,
A1 - Xing-Yu Wang,
A1 - M. Mahfouf,
A1 - D.A. Linkens,
PY - 2008
KW - Operator functional states
KW - human-machine system
KW - automation-enhanced cabin air management system (aCAMS)
KW - ANFIS
KW - genetic algorithm
VL - 1
JA - BioMedical Engineering and Informatics, International Conference on
ER -
 
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.
Index Terms:
Operator functional states, human-machine system, automation-enhanced cabin air management system (aCAMS), ANFIS, genetic algorithm
Citation:
Jian-Hua Zhang, Xing-Yu Wang, M. Mahfouf, D.A. Linkens, "Fuzzy Logic based Identification of Operator Functional States Using Multiple Physiological and Performance Measures," bmei, vol. 1, pp.570-574, 2008 International Conference on BioMedical Engineering and Informatics, 2008
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