Review Article Open Access

EEG-based Processing and Classification Methodologies for Autism Spectrum Disorder: A Review

Gunavaran Brihadiswaran1, Dilantha Haputhanthri1, Sahan Gunathilaka1, Dulani Meedeniya1 and Sampath Jayarathna2
  • 1 University of Moratuwa, Sri Lanka
  • 2 Old Dominion University, United States


Autism Spectrum Disorder is a lifelong neurodevelopmental condition which affects social interaction, communication and behaviour of an individual. The symptoms are diverse with different levels of severity. Recent studies have revealed that early intervention is highly effective for improving the condition. However, current ASD diagnostic criteria are subjective which makes early diagnosis challenging, due to the unavailability of well-defined medical tests to diagnose ASD. Over the years, several objective measures utilizing abnormalities found in EEG signals and statistical analysis have been proposed. Machine learning based approaches provide more flexibility and have produced better results in ASD classification. This paper presents a survey of major EEG-based ASD classification approaches from 2010 to 2018, which adopt machine learning. The methodology is divided into four phases: EEG data collection, pre-processing, feature extraction and classification. This study explores different techniques and tools used for pre-processing, feature extraction and feature selection techniques, classification models and measures for evaluating the model. We analyze the strengths and weaknesses of the techniques and tools. Further, this study summarizes the ASD classification approaches and discusses the existing challenges, limitations and future directions.

Journal of Computer Science
Volume 15 No. 8, 2019, 1161-1183


Submitted On: 29 June 2019 Published On: 23 August 2019

How to Cite: Brihadiswaran, G., Haputhanthri, D., Gunathilaka, S., Meedeniya, D. & Jayarathna, S. (2019). EEG-based Processing and Classification Methodologies for Autism Spectrum Disorder: A Review. Journal of Computer Science, 15(8), 1161-1183.

  • 70 Citations



  • Autism Spectrum Disorder
  • Machine Learning
  • EEG