Quantitative EEG features selection in the classification of attention and response control in the children and adolescents with attention deficit hyperactivity disorder

Azadeh Bashiri; Leila Shahmoradi; Hamid Beigy; Behrouz A Savareh; Masood Nosratabadi; Sharareh R N Kalhori; Marjan Ghazisaeedi

doi:10.4155/fsoa-2017-0138

Quantitative EEG features selection in the classification of attention and response control in the children and adolescents with attention deficit hyperactivity disorder

Future Sci OA. 2018 Feb 14;4(5):FSO292. doi: 10.4155/fsoa-2017-0138. eCollection 2018 Jun.

Authors

Azadeh Bashiri^{1

1}, Leila Shahmoradi^{1

1}, Hamid Beigy^{2

2}, Behrouz A Savareh^{3

3}, Masood Nosratabadi^{4

4}, Sharareh R N Kalhori^{1

1}, Marjan Ghazisaeedi^{1

1}

Affiliations

¹ Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
² Department of Computer Engineering, Sharif University of Technology, Tehran, Iran.
³ Student Research Committee, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
⁴ Department of Clinical Psychology, University of Social Welfare & Rehabilitation Sciences, Tehran, Iran.

Abstract

Aim: Quantitative EEG gives valuable information in the clinical evaluation of psychological disorders. The purpose of the present study is to identify the most prominent features of quantitative electroencephalography (QEEG) that affect attention and response control parameters in children with attention deficit hyperactivity disorder.

Methods: The QEEG features and the Integrated Visual and Auditory-Continuous Performance Test ( IVA-CPT) of 95 attention deficit hyperactivity disorder subjects were preprocessed by Independent Evaluation Criterion for Binary Classification. Then, the importance of selected features in the classification of desired outputs was evaluated using the artificial neural network.

Results: Findings uncovered the highest rank of QEEG features in each IVA-CPT parameters related to attention and response control.

Conclusion: Using the designed model could help therapists to determine the existence or absence of defects in attention and response control relying on QEEG.

Keywords: ADHD; IVA-CPT; QEEG.