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Evaluation of EEG Synchronization in Autistic Children Using Cross-Sample Entropy and Cross-Approximate Entropy
Current Issue
Volume 2, 2015
Issue 1 (January)
Pages: 1-9   |   Vol. 2, No. 1, January 2015   |   Follow on         
Paper in PDF Downloads: 27   Since Aug. 28, 2015 Views: 1552   Since Aug. 28, 2015
Authors
[1]
Sara Bagherzadeh, Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
[2]
Ali Sheikhani, Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
[3]
Hamid Behnam, Electrical Engineering Department, Iran University of Science & Technology, Tehran, Iran.
Abstract
Autism is a pervasive developmental disorder that strongly affects lifestyle of autistic person. This disorder involves communication, social interaction and repetitive behaviors. There are several methods which evaluate EEG signals of autistic children. We used a relatively new method based on cross entropies to evaluate synchrony in these children. In this study, EEG signals of 14 autistic children and 14 normal children in 8-11 years of old were evaluated using two non-linear features: cross-approximate entropy and cross-sample entropy. These features are extracted from 171 pairs of electrodes in each EEG frequency bands. To our knowledge, this is the first time that these features of synchronization are performed to evaluate autism disorder. Results of evaluation using t-test and then area under curves values of receiver operation characteristic curves showed that cross-approximate entropy have significant differences between two groups with lower values mostly in left hemisphere of autistic children in alpha, beta and gamma frequency bands and cross-sample entropy have widespread significant differences between the groups with lower values in alpha frequency band. Also, there were no significant differences in delta and theta frequency bands. This evaluation of EEG signals at pairs of electrodes is a synchronization measure of brain functions. Non-linear features have been used to evaluate EEG signals of autistic children. Cross-Approximate entropy and cross-Sample entropy can be used for evaluation of autism disorder. There were more synchrony in pairs of electrodes at alpha frequency band of autistic children compare to normal children. These findings can be used for quantitatively discriminate autistic children.
Keywords
EEG, Autism Disorder, Cross-Sample Entropy, Cross- Approximate Entropy, Synchronization
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