Support vector machine with theta-beta band power features generated from writing of dyslexic children

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Support vector machine with theta-beta band power features generated from writing of dyslexic children

The classification of dyslexia using EEG requires the detection of subtle differences between groups of children in an environment that are known to be noisy and full of artifacts. It is thus necessary for the feature extraction to improve the classification. The normal and poor dyslexic are found t...

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Bibliographic Details
Published in:	International Journal of Integrated Engineering
Main Author:	Mahmoodin Z.; Lee K.Y.; Mansor W.; Zainuddin A.Z.A.
Format:	Article
Language:	English
Published:	Penerbit UTHM 2019
Online Access:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075880383&doi=10.30880%2fijie.2019.11.03.005&partnerID=40&md5=d3e80edae76546f5c4a7bce69c9e5e7e

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