@conference{Shams2013,
title = {Source-temporal-features for detection EEG behavior of autism spectrum disorder},
author = {W K Shams and A Wahab},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84879037124&doi=10.1109%2fICT4M.2013.6518913&partnerID=40&md5=db31715811e1e8fdf62c9d61daf8e6f6},
doi = {10.1109/ICT4M.2013.6518913},
isbn = {9781479901340},
year = {2013},
date = {2013-01-01},
journal = {2013 5th International Conference on Information and Communication Technology for the Muslim World, ICT4M 2013},
abstract = {This study introduces a new model to capture the abnormal brain activity of children with Autism Spectrum Disorder (ASD) during eyes open and eyes closed resting conditions. EEG data was collected from normal subjects' ages (4 to 9) years and ASD subjects match group. Time Difference of Arrival (TDOA) approach was applied with EEG data raw for feature extracted at time domain. The neural network, Multilayer Perception (MLP) was used to distinguish between the two groups during the two tasks. Results show significant accuracy around 98% for both tasks and clearly discriminate for the features in z-dimension his electronic document is a "live" template and already defines the components of your paper [title, text, heads, etc.] in its style sheet. © 2013 IEEE.},
note = {cited By 1},
keywords = {ASD, Autism Spectrum Disorders, Brain Activity, Children with Autism, Classification (of information), Communication, Diseases, Electroencephalography, Electronic Document, Information Technology, Multi-Layer Perception, Temporal Features, Time Difference of Arrival},
pubstate = {published},
tppubtype = {conference}
}