A Survey of Attention Deficit Hyperactivity Disorder Identification Using Psychophysiological Data

Authors

DOI:

https://doi.org/10.3991/ijoe.v15i13.10744

Keywords:

Attention Deficit Hyperactivity Disorder, eye movements, fMRI, decision support system, comparative study

Abstract


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.

Author Biographies

Senuri De Silva, Department of Computer Science and Engineering, University of Moratuwa

Ms. S. De Silva is an undergraduate student at the, University of Moratuwa, Sri Lanka. She has research experience in Biomedical and Machine learning.

Sanuwani Dayarathna, Department of Computer Science and Engineering, University of Moratuwa

Ms. S. Dayarathna is an undergraduate student at the University of Moratuwa, Sri Lanka. She has research experience in Biomedical, Machine Learning and Data Mining.

Gangani Ariyarathne, Department of Computer Science and Engineering, University of Moratuwa

Ms. G. Ariyarathne is an undergraduate student at University of Moratuwa, Sri Lanka. She has research experience in Machine Learning, Data Mining, Biomedical and Computer Security.

Dulani Meedeniya, University of Moratuwa

Dr. D. Meedeniya is a Senior Lecturer in the Department of Computer Science and Engineering, at the University of Moratuwa, Sri Lanka. She holds a PhD in Computer Science from the University of St Andrews, United Kingdom. Her main research interests are Software modelling and design, Workflow tool support for bioinformatics, Data Visualization and Recommender systems. She is a Fellow of HEA(UK), MIET, MIEEE and a Charted Engineer registered at EC (UK).

Sampath Jayarathna, Department of Computer Science, Old Dominion University,

Dr. S. Jayarathne is an Assistant Professor at the Department of Computer Science, College of Science, Old Dominion University, Norfolk, VA. He received his Ph.D. from Texas A&M University. His research interests include data science, information retrieval and machine learning.

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Published

2019-09-30

How to Cite

De Silva, S., Dayarathna, S., Ariyarathne, G., Meedeniya, D., & Jayarathna, S. (2019). A Survey of Attention Deficit Hyperactivity Disorder Identification Using Psychophysiological Data. International Journal of Online and Biomedical Engineering (iJOE), 15(13), pp. 61–76. https://doi.org/10.3991/ijoe.v15i13.10744

Issue

Vol. 15 No. 13 (2019)

Section

Papers