An Efficient Approach for Detection of Autism Spectrum Disorder Using Electroencephalography Signal

Abstract

Autism spectrum disorder is a brain disorder in children and is detected using magnetic resonance imaging scan and electroencephalography (EEG) signals. This paper presents a system to detect autism using EEG signals. It uses pre-recorded EEG signal, preprocesses it using a digital filter, and extracts features in time and frequency domain using discrete wavelet transform. The features obtained are given to classifiers such as neural networks, support vector machine, K-nearest neighbour (KNN), subspace KNN, and linear discriminant analysis. The results show that the use of subspace KNN provides the best accuracy of 92.8% for time-domain features.

KEYWORDS:

• Autism
• Classifiers
• DWT
• FIR filter
• IIR filter
• Subspace KNN

Additional information

Notes on contributors

Tulikapriya Sinha

Tulikapriya Sinha has currently completed Master of Engineering from Pune Institute of Computer Technology in electronics and telecommunication domain with specialization in microwave communication. She completed her Bachelors of Technology in electronics and telecommunication from Symbiosis Institute of Technology. Her domain of interests are signal processing, biomedical, wireless communication and artificial intelligence.

Mousami V. Munot

Mousami V Munot has completed MTech from College of Engineering, Pune, CoEP (1st rank holder) in 2007. Savitribai Phule Pune University has awarded her a PhD degree in November, 2013. She is a member of ISTE, BMESI and IoE. She is at present the SARB-member and global operations chair and represented India in various international platforms. Her research interests are medical imaging, artificial intelligence and machine learning. E-mail: [email protected]

R. Sreemathy

R Sreemathy is working as associate professor in Pune Institute of Computer Technology, Savitribai Phule Pune University, India. She has her master’s degree in electronics engineering from college of Engineering, Savitribai Phule Pune University and doctoral degree in electronics engineering from Shivaji University, India. Her research areas include signal processing, image processing, antenna design and wireless communication. E-mail: [email protected]