Volume 8, Issue 3 (August 2021)                   Avicenna J Neuro Psycho Physiology 2021, 8(3): 115-123 | Back to browse issues page


XML Print


1- Bachelor of Biomedical Engineering, Imam Reza International University, Iran, Mashhad
2- International University of Imam Reza (AS) , g.sadeghi@imamreza.ac.ir
3- Master of Biomedical Engineering, Islamic Azad University of Mashhad, Iran, Mashhad
Abstract:   (1121 Views)
This study aimed to examine the brain signals of children with Autism Spectrum Disorder (ASD) and use a method according to the concept of complementary opposites to obtain the prominent features or a pattern of EEG signal that represents the biological characteristic of such children. In this study, 20 children with the mean±SD age of 8±5 years were divided into two groups of normal control (NC) and ASD. The diagnosis and approval of individuals in both groups were conducted by two experts in the field of pediatric psychiatry and neurology. The recording protocol was designed with the most accuracy; therefore, the brain signals were recorded with the least noise in the awake state of the individuals in both groups. Moreover, the recording was conducted in three stages from two channels (C3-C4) of EEG ( referred to as the central part of the brain) which were symmetrical in function. In this study, the Mandala method was adopted based on the concept of complementary opposites to investigate the features extracted from Mandala pattern topology and obtain new features and pseudo-patterns for the screening and early diagnosis of ASD. The optimal feature here was based on different stages of processing and statistical analysis of Pattern Detection Capability (PDC). The PDC is a biomarker derived from the Mandala pattern for differentiating the NC from ASD groups.
Full-Text [PDF 1027 kb]   (458 Downloads) |   |   Full-Text (HTML)  (289 Views)  
Article Type: Research Article | Subject: Child / Geriatric Psychiatry
Received: 2020/03/27 | Accepted: 2020/09/14 | Published: 2021/06/20

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.