DocumentCode
547660
Title
Detecting ADHD children using symbolic dynamic of nonlinear features of EEG
Author
Allahverdy, A. ; Nasrabadi, Ali Moti ; Mohammadi, Mohammad Reza
Author_Institution
Shahed University
fYear
2011
fDate
17-19 May 2011
Firstpage
1
Lastpage
4
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
Electrodes; Electroencephalography; Feature extraction; Fractals; Pediatrics; Scalp; Time series analysis; ADHD; nonlinear feature; symbolic dynamic;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical Engineering (ICEE), 2011 19th Iranian Conference on
Conference_Location
Tehran, Iran
Print_ISBN
978-1-4577-0730-8
Electronic_ISBN
978-964-463-428-4
Type
conf
Filename
5955548
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