Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/57697
Title: Recurrence Quantification Analysis of EEG signals for Children with ASD
Authors: Menaka, R
Aarthy, M Thanga
Chavan, Renuka Mahadev
Perumal, R C
Menon, Mahima S
Keywords: Autism Spectrum Disorder;Auditory/visual;Distance metric;Electroencephalogram;Fixed amount of nearest neighbor
Issue Date: May-2021
Publisher: NISCAIR-CSIR, India
Abstract: The present study aims at identifying the brain response for auditory/visual stimuli in typically developing (TD) and children with autism through electroencephalography (EEG). Early diagnoses do help in customized training and progressing the children in regular stream. To reveal the underlying brain dynamics, non-linear analysis was employed. In the current study, Recurrent Quantification Analysis (RQA) with varying parameters was analyzed. For better information retrieval, cosine distance metric is additionally considered for analysis and compared with other distance metrics in RQA. Each computational combination of RQA is measured and the responding channels were analyzed and discussed. It was observed that the FAN neighborhood with cosine distance parameters was able to discriminate between ASD and TD prominently.
Page(s): 438-448
URI: http://nopr.niscair.res.in/handle/123456789/57697
ISSN: 0975-1084 (Online); 0022-4456 (Print)
Appears in Collections:JSIR Vol.80(05) [May 2021]

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