EEG Signal Analysis of Writing and Typing between Adults with Dyslexia and Normal Controls

TitleEEG Signal Analysis of Writing and Typing between Adults with Dyslexia and Normal Controls
Publication TypeJournal Article
Year of Publication2018
AuthorsPerera, H., M. F. Shiratuddin, K. W. Wong, and K. Fullarton
JournalInternational Journal of Interactive Multimedia and Artificial Intelligence
ISSN1989-1660
IssueRegular Issue
Volume5
Number1
Date Published06/2018
Pagination62-67
Abstract

EEG is one of the most useful techniques used to represent behaviours of the brain and helps explore valuable insights through the measurement of brain electrical activity. Hence, plays a vital role in detecting neurological conditions. In this paper, we identify some unique EEG patterns pertaining to dyslexia, which is a learning disability with a neurological origin. Although EEG signals hold important insights of brain behaviours, uncovering these insights are not always straightforward due to its complexity. We tackle this using machine learning and uncover unique EEG signals generated in adults with dyslexia during writing and typing as well as optimal EEG electrodes and brain regions for classification. This study revealed that the greater level of difficulties seen in individuals with dyslexia during writing and typing compared to normal controls are reflected in the brainwave signal patterns.

KeywordsClassification, Dyslexia, Electroencephalography, Machine Learning, Support Vector Machine
DOI10.9781/ijimai.2018.04.005
URLhttp://www.ijimai.org/journal/sites/default/files/files/2018/04/ijimai_5_1_8_pdf_17747.pdf
AttachmentSize
ijimai_5_1_8.pdf1.37 MB