Detecting ADHD Children Using Symbolic Dynamic of Nonlinear Features of EEG

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:

ADHD , nonlinear feature , symbolic dynamic