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,...
| Autores: | , , , , , , , |
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| 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 |
| 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. |
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