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DIAGNOSIS OF AUTISM IN CHILDREN USING DEEP NEURAL NETWORKS

Abstract The autism spectrum disorder is a common term for a group of complex brain and neurodevelopment disorder. The EEG medical imaging technique is a perfect tool for the brain signal analysis. In this study, we identify the variations in EEG signals on the auto-regressive features for classifying the normal and autistic features using Artificial Neural Networks. The simulation result shows that the proposed DNN in classifying the autism features achieves a classification rate of 95.23%. Authors N V Kousik Galgotia University, India Keywords Autism Disorder, Auto Regressive Features, Electroencephalography, ANN

Published By : ICTACT Published In : ICTACT Journal on Data Science and Machine Learning ( Volume: 1 , Issue: 2 ) Date of Publication : March 2020