A Review on Diagnosis of Autism Spectrum Disorder using EEG based on the Machine Learning Techniques
Abstract
Autism Spectrum Disorder (ASD) is a developmental disorder that affects the behavioral and psychological functioning of an individual. The early intervention of ASD significantly improves and may normalize the brain function of children with autism. Electroencephalography (EEG) is one of the fundamental tools for diagnosing and identifying ASD. In recent days, EEG is being used widely by the researchers for diagnosing ASD. A survey has been prepared, which analyzes the EEG based on pattern recognition techniques. In this paper, a brief study of various methods for diagnosing autism spectrum disorder is given. Also, difficulties and feature investigations are examined.
Keywords-autism spectrum disorder; feature extraction; classification; electroencephalography; Machine Learning.