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International Conference on Neural Information Processing

ICONIP 2016: Neural Information Processing pp 626–635Cite as

A Review of Electroencephalogram-Based Analysis and Classification Frameworks for Dyslexia

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9950))

Abstract

Dyslexia is a hidden learning disability that causes difficulties in reading and writing despite average intelligence. Electroencephalogram (EEG) is one of the upcoming methods being researched for identifying unique brain activation patterns in dyslexics. This paper examines pros and cons of existing EEG-based analysis and classification frameworks for dyslexia and recommends optimizations through the findings to assist future research.

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Authors and Affiliations

  1. School of Engineering and Information Technology, Murdoch University, Murdoch, Australia

    Harshani Perera, Mohd Fairuz Shiratuddin & Kok Wai Wong

Authors
  1. Harshani Perera
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  2. Mohd Fairuz Shiratuddin
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  3. Kok Wai Wong
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Corresponding author

Correspondence to Harshani Perera .

Editor information

Editors and Affiliations

  1. The University of Tokyo , Tokyo, Japan

    Akira Hirose

  2. Kobe University , Kobe, Japan

    Seiichi Ozawa

  3. Okinawa Institute of Science and Technology Graduate University, Onna, Japan

    Kenji Doya

  4. Nara Institute of Science and Technology , Ikoma, Japan

    Kazushi Ikeda

  5. Kyungpook National University , Daegu, Korea (Republic of)

    Minho Lee

  6. Chinese Academy of Sciences , Beijing, China

    Derong Liu

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© 2016 Springer International Publishing AG

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Perera, H., Shiratuddin, M.F., Wong, K.W. (2016). A Review of Electroencephalogram-Based Analysis and Classification Frameworks for Dyslexia. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9950. Springer, Cham. https://doi.org/10.1007/978-3-319-46681-1_74

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  • DOI: https://doi.org/10.1007/978-3-319-46681-1_74

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46680-4

  • Online ISBN: 978-3-319-46681-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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