期刊
4TH INTERNATIONAL CONFERENCE OF COGNITIVE SCIENCE
卷 32, 期 -, 页码 148-152出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.sbspro.2012.01.024
关键词
Attention-Deficit Hyperactivity Disorder (ADHD); K-nearest neighbors classifier; Continuous Performance Test (CPT); electroencephalogram; feature extraction; sustained attention
This study investigates the non-linear features of electroencephalogram signals regarding ADHD and normal adult participants while performing Continuous Performance Test. Three non-linear features were extracted from the EEG signals. ADHD and age-matched normal groups were investigated separately which revealed that there is a significant relation between clinical presentation of the participants and some non-linear features. The accuracy of 88% and 96% were achieved in classification of clinical and non-clinical participants using one and two features respectively. The best classification result was obtained with a combination of two features in Wavelet-Entropy group. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the 4th International Conference of Cognitive Science
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