Developing an eye-tracking algorithm as a potential tool for early diagnosis of autism spectrum disorder in children

Autism spectrum disorder (ASD) currently affects nearly 1 in 160 children worldwide. In over two-thirds of evaluations, no validated diagnostics are used and gold standard diagnostic tools are used in less than 5% of evaluations. Currently, the diagnosis of ASD requires lengthy and expensive tests,...

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Detalles Bibliográficos
Autores: Vargas-Cuentas, NI, Roman-Gonzalez, A, Gilman, RH, Barrientos, F, Ting, J, Hidalgo, D, Jensen, K, Zimic, M
Tipo de recurso: artículo
Fecha de publicación:2017
País:Perú
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Idioma:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/964
Acceso en línea:https://hdl.handle.net/20.500.12390/964
https://doi.org/10.1371/journal.pone.0188826
Access Level:acceso abierto
Palabra clave:Diagnostico
Algoritmo
Autismo
https://purl.org/pe-repo/ocde/ford#3.02.24
Descripción
Sumario:Autism spectrum disorder (ASD) currently affects nearly 1 in 160 children worldwide. In over two-thirds of evaluations, no validated diagnostics are used and gold standard diagnostic tools are used in less than 5% of evaluations. Currently, the diagnosis of ASD requires lengthy and expensive tests, in addition to clinical confirmation. Therefore, fast, cheap, portable, and easy-to-administer screening instruments for ASD are required. Several studies have shown that children with ASD have a lower preference for social scenes compared with children without ASD. Based on this, eye-tracking and measurement of gaze preference for social scenes has been used as a screening tool for ASD. Currently available eye-tracking software requires intensive calibration, training, or holding of the head to prevent interference with gaze recognition limiting its use in children with ASD.