Modeling the mental differentiation task with EEG
Date
2012
Authors
Vo, Tan
Gedeon, Tamas (Tom)
Tran, Dat
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Abstract
Differentiation in human beings is the act of perceiving the difference in or between objects. In other words, it is the mental process taking place to discriminate one thing from others, a common task performed by a person on a very regular basis. Making such differentiations, small or large, easy or hard, still requires a combination of cognitive processes to occur across various parts of the human brain. In this paper, an EEG-based BCI experiment was organized to study the detection of such cognitive processes. Utilizing a machine learning tool, Artificial Neural Networks, to aid in analyzing the acquired dataset, a high correct classification rate was achieved, confirming that it is possible to computationally detect these differentiation activities from EEG signals.
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Keywords
Keywords: Artifical neural networks; BCI; Biosignal processing; Classification rates; Cognitive process; Data sets; Differencitation tasks; EEG signals; Human being; Human brain; Mental process; Cognitive systems; Data processing; Electroencephalography; Neural net Artifical neural network; BCI; Biosignal processing; Differencitation tasks; EEG
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Source
Proceedings of ICONIP 2012
Type
Conference paper
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Entity type
Access Statement
Open Access
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Restricted until
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