Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/57697
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dc.contributor.authorMenaka, R-
dc.contributor.authorAarthy, M Thanga-
dc.contributor.authorChavan, Renuka Mahadev-
dc.contributor.authorPerumal, R C-
dc.contributor.authorMenon, Mahima S-
dc.date.accessioned2021-07-12T11:29:25Z-
dc.date.available2021-07-12T11:29:25Z-
dc.date.issued2021-05-
dc.identifier.issn0975-1084 (Online); 0022-4456 (Print)-
dc.identifier.urihttp://nopr.niscair.res.in/handle/123456789/57697-
dc.description438-448en_US
dc.description.abstractThe 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.en_US
dc.language.isoenen_US
dc.publisherNISCAIR-CSIR, Indiaen_US
dc.sourceJSIR Vol.80(05) [May 2021]en_US
dc.subjectAutism Spectrum Disorderen_US
dc.subjectAuditory/visualen_US
dc.subjectDistance metricen_US
dc.subjectElectroencephalogramen_US
dc.subjectFixed amount of nearest neighboren_US
dc.titleRecurrence Quantification Analysis of EEG signals for Children with ASDen_US
dc.typeArticleen_US
Appears in Collections:JSIR Vol.80(05) [May 2021]

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