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Modeling the Mental Differentiation Task with EEG

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7664)

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.

Keywords

  • BCI
  • Artifical neural network
  • Differencitation tasks
  • EEG
  • Biosignal processing

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© 2012 Springer-Verlag Berlin Heidelberg

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Vo, T., Gedeon, T., Tran, D. (2012). Modeling the Mental Differentiation Task with EEG. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7664. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34481-7_44

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  • DOI: https://doi.org/10.1007/978-3-642-34481-7_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34480-0

  • Online ISBN: 978-3-642-34481-7

  • eBook Packages: Computer ScienceComputer Science (R0)