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

• Autores: Vargas-Cuentas, NI, Roman-Gonzalez, A, Gilman, RH, Barrientos, F, Ting, J, Hidalgo, D, Jensen, K, Zimic, M
• Formato: artículo
• Fecha de Publicación: 2017
• Institución: Consejo Nacional de Ciencia Tecnología e Innovación
• Repositorio: CONCYTEC-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.concytec.gob.pe:20.500.12390/964
• Enlace del recurso: https://hdl.handle.net/20.500.12390/964; https://doi.org/10.1371/journal.pone.0188826
• Nivel de acceso: acceso abierto
• Materia: Diagnostico; Algoritmo; Autismo; https://purl.org/pe-repo/ocde/ford#3.02.24

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.