NDLI: Diagnosis of autism spectrum disorder from EEG using a time–frequency spectrogram image-based approach

Content Provider	IET Digital Library
Author	Tawhid, M. N. A. Siuly, S. Wang, H.
Abstract	Autism is a type of neurodevelopment disorder in which individuals often have difficulties in social relationship, communication, expressing and controlling emotions and poor eye contact, among other symptoms. Currently, electroencephalography (EEG) is the most popular tool to investigate the presence of autism biomarkers. Generally, EEG recordings generate huge volume data with dynamic behaviour. In current practice, the massive EEG data are visually analysed by specialist clinicians to identify autism, which is time consuming, costly, subject to human error, and reduces decision-making reliability. Hence this Letter aims to develop an efficient autism diagnostic system that can automatically identify autism based on time–frequency spectrogram images from EEG signals. Firstly, the raw EEG data is pre-processed using several techniques, such as re-referencing, filtering and normalisation. After that, the pre-processed EEG signals are converted to two-dimensional images using a short-time Fourier transform. Then, textural features are extracted, and significant features are selected using principal component analysis, and feed to support vector machine classifier for classification. The proposed system achieved an average of 95.25% accuracy in ten-fold cross-validation evaluation. The developed system's simplicity and performance indicates usefulness as a decision support tool for healthcare professionals in autism diagnosis.
Starting Page	1372
Ending Page	1375
Page Count	4
ISSN	00135194
Volume Number	56
e-ISSN	1350911X
Issue Number	Issue 25, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/56/25
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2020.2646
Journal	Electronics Letters
Publisher Date	2020-10-08
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Autism Biomarkers Autism Diagnostic System Autism Spectrum Disorder Bioelectric Signal Biology And Medical Computing Computer Vision And Image Processing Technique Decision Support Tool Decision-making Reliability Dynamic Behaviour EEG Signal Pre-processing Electrical Activity in Neurophysiological Processes Electrodiagnostics And Other Electrical Measurement Technique Electroencephalography Eye Contact Feature Extraction Feature Selection Fourier Transforms Image Classification Image Recognition Medical Disorders Medical Image Processing Neurodevelopment Disorder Neurophysiology Optical, Image And Video Signal Processing Principal Component Analysis Probability Theory Short-time Fourier Transform Social Relationship Statistics Stochastic Linearised SCUC Support Vector Machine Ten-fold Cross-validation Evaluation Textural Feature Extraction Time-frequency Spectrogram Image-based Approach Two-dimensional Image
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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