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...
| Published in: | International Journal of Integrated Engineering |
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| Main Author: | |
| Format: | Article |
| Language: | English |
| Published: |
Penerbit UTHM
2019
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| 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 |