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Cognitive Neurodynamics
Erschienen in: Cognitive Neurodynamics 6/2013

01.12.2013 | Research Article

Classifying human operator functional state based on electrophysiological and performance measures and fuzzy clustering method

verfasst von: Jian-Hua Zhang, Xiao-Di Peng, Hua Liu, Jörg Raisch, Ru-Bin Wang

Erschienen in: Cognitive Neurodynamics | Ausgabe 6/2013

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Abstract

The human operator’s ability to perform their tasks can fluctuate over time. Because the cognitive demands of the task can also vary it is possible that the capabilities of the operator are not sufficient to satisfy the job demands. This can lead to serious errors when the operator is overwhelmed by the task demands. Psychophysiological measures, such as heart rate and brain activity, can be used to monitor operator cognitive workload. In this paper, the most influential psychophysiological measures are extracted to characterize Operator Functional State (OFS) in automated tasks under a complex form of human–automation interaction. The fuzzy c-mean (FCM) algorithm is used and tested for its OFS classification performance. The results obtained have shown the feasibility and effectiveness of the FCM algorithm as well as the utility of the selected input features for OFS classification. Besides being able to cope with nonlinearity and fuzzy uncertainty in the psychophysiological data it can provide information about the relative importance of the input features as well as the confidence estimate of the classification results. The OFS pattern classification method developed can be incorporated into an adaptive aiding system in order to enhance the overall performance of a large class of safety–critical human–machine cooperative systems.
Vorheriger Artikel Perception of successive brief objects as a function of stimulus onset asynchrony: model experiments based on two-stage synchronization of neuronal oscillators
Nächster Artikel Coupling-induced population synchronization in an excitatory population of subthreshold Izhikevich neurons

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Metadaten
Titel
Classifying human operator functional state based on electrophysiological and performance measures and fuzzy clustering method
verfasst von
Jian-Hua Zhang
Xiao-Di Peng
Hua Liu
Jörg Raisch
Ru-Bin Wang
Publikationsdatum
01.12.2013
Verlag
Springer Netherlands
Erschienen in
Cognitive Neurodynamics / Ausgabe 6/2013
Print ISSN: 1871-4080
Elektronische ISSN: 1871-4099
DOI
https://doi.org/10.1007/s11571-013-9243-3

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