Detecting ADHD children using symbolic dynamic of nonlinear features of EEG

Author

Allahverdy, A. ; Nasrabadi, A.M. ; Mohammadi, Mohammad Reza

Author_Institution

Shahed Univ., Tehran, Iran

fYear

2011

fDate

17-19 May 2011

Firstpage

1

Lastpage

1

Abstract

Attention deficit hyperactivity disorder (AD/HD) in children and adolescents is characterized by excessive restlessness and extremely poor concentration span, resulting in impulsive and disruptive behavior. Using a time series obtained from the electroencephalogram of ADHD children in visual task, we show that continuity of attention in ADHD and Control group children is different. In this study we extract nonlinear feature of EEG time series of ADHD and control group then using symbolic dynamic we obtain to a relative reliable accurate classification. Classification accuracy is 86%. This method is reliable for classification between ADHD and control group.

Keywords

behavioural sciences; electroencephalography; medical disorders; medical signal processing; paediatrics; signal classification; symbol manipulation; time series; EEG nonlinear feature symbolic dynamics; EEG time series; attention continuity; attention deficit hyperactivity disorder; disruptive behavior; electroencephalogram; excessive restlessness; feature classification; impulsive behavior; paediatric ADHD detection; poor concentration span; visual task; ADHD; nonlinear feature; symbolic dynamic;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Engineering (ICEE), 2011 19th Iranian Conference on

Conference_Location

Tehran

Print_ISBN

978-1-4577-0730-8

Type

conf

Filename

5955875