A Survey of Attention Deficit Hyperactivity Disorder Identification Using Psychophysiological Data

Ecolinguística: Revista brasileira de ecologia e linguagem

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Title A Survey of Attention Deficit Hyperactivity Disorder Identification Using Psychophysiological Data
 
Creator De Silva, Senuri; Department of Computer Science and Engineering, University of Moratuwa
Dayarathna, Sanuwani; Department of Computer Science and Engineering, University of Moratuwa
Ariyarathne, Gangani; Department of Computer Science and Engineering, University of Moratuwa
Meedeniya, Dulani; University of Moratuwa
Jayarathna, Sampath; Department of Computer Science, Old Dominion University,
 
Subject Attention Deficit Hyperactivity Disorder; eye movements; fMRI; decision support system; comparative study
 
Description Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurological disorders among children, that affects different areas in the brain that allows executing certain functionalities. This may lead to a variety of impairments such as difficulties in paying attention or focusing, controlling impulsive behaviors and overreacting. The continuous symptoms may have a severe impact in the long-term. This paper discusses the existing literature on the identification of ADHD using eye movement data and fMRI together including different deep learning techniques, existing models and a thorough analysis of the existing literature. We have identified the current challenges and possible future directions to provide computational support for early identification of ADHD patients that enable early treatments.
 
Publisher kassel university press GmbH
 
Contributor
 
Date 2019-09-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier https://online-journals.org/index.php/i-joe/article/view/10744
10.3991/ijoe.v15i13.10744
 
Source International Journal of Online and Biomedical Engineering (iJOE); Vol 15, No 13 (2019); pp. 61-76
2626-8493
 
Language eng
 
Relation https://online-journals.org/index.php/i-joe/article/view/10744/5938
 
Rights Copyright (c) 2019 Senuri De Silva, Sanuwani Dayarathna, Gangani Ariyarathne, Dulani Meedeniya, Sampath Jayarathne
 

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