Early identification of dyslexic preschoolers based on neurophysiological signals

• Published in: Proceedings - 2013 International Conference on Advanced Computer Science Applications and Technologies, ACSAT 2013
• Main Author: Karim I.; Qayoom A.; Wahab A.; Kamaruddin N.
• Format: Conference paper
• Language: English
• Published: IEEE Computer Society 2013
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904160873&doi=10.1109%2fACSAT.2013.78&partnerID=40&md5=89fad7f850bf7ba6cc9f74a1f7c4ae5a

Dyslexia is a learning difficulty and in most cases cannot be identified until a child is already in the third grade or later. At this time a dyslexic child have only an one-in-seven chance of ever catching up with his or her peers in reading, writing, speaking or listening. Early identification can pave the way for early intervention and the dyslexic child can be helped at an early stage. Furthermore, the results yielded are the best when the intervention in the form of providing specialized instructions or carried out through some other way yields best results when done at preschoolers. Thus the importance of early identification. The following study is devoted to the EEG based identification of dyslexia for preschool going children. In this analysis feature extraction are carried out using KDE and MLP is used for classification of the features extracted. The results show promising classification accuracy. © 2013 IEEE.