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%.