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

Perera, H., Shiratuddin, M.F. and 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. and Liu, D., (eds.) Neural Information Processing: 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part IV. Springer International Publishing, pp. 626-635.

Link to Published Version: http://dx.doi.org/10.1007/978-3-319-46681-1_74
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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.

Item Type: Book Chapter
Murdoch Affiliation(s): School of Engineering and Information Technology
Publisher: Springer International Publishing
Copyright: 2016 Springer International Publishing AG
Other Information: Series Title: Lecture Notes in Computer Science; Vol. No. 9948; ISSN: 0302-9743
URI: http://researchrepository.murdoch.edu.au/id/eprint/34633
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