Towards an automatic early screening system for autism spectrum disorder in toddlers based on eye‑tracking

According to official estimations, autism spectrum disorder (ASD) affects around 1% of European newborns. The high level of dependency of ASD-affected subjects entails an extremely high social and economic cost. However, early intervention can drastically improve children’s development and thus redu...

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Autores: Fernández Lanvin, Daniel|||0000-0002-5666-9809, González Rodríguez, Bernardo Martín|||0000-0002-9695-3919, Andrés Suárez, Javier|||0000-0001-6887-4087, Camero, Raquel
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universidad de Oviedo (UNIOVI)
Repositorio:RUO. Repositorio Institucional de la Universidad de Oviedo
Idioma:inglés
OAI Identifier:oai:digibuo.uniovi.es:10651/70462
Acceso en línea:https://hdl.handle.net/10651/70462
https://dx.doi.org/10.1007/s11042-023-17694-8
Access Level:acceso abierto
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spelling Towards an automatic early screening system for autism spectrum disorder in toddlers based on eye‑tracking Fernández Lanvin, Daniel|||0000-0002-5666-9809 González Rodríguez, Bernardo Martín|||0000-0002-9695-3919 Andrés Suárez, Javier|||0000-0001-6887-4087 Camero, Raquel According to official estimations, autism spectrum disorder (ASD) affects around 1% of European newborns. The high level of dependency of ASD-affected subjects entails an extremely high social and economic cost. However, early intervention can drastically improve children’s development and thus reduce their dependency. One of the main common characteristics of subjects with ASD is difficulties with social interaction, which determines how they react to certain stimuli. This behavior can be automatically detected by analyzing their gaze. This study explores and evaluates the feasibility of automatic screening for ASD in toddlers under 24 months of age based on this specific behavior. We applied a matched pairs experimental design and a set of test videos, using a set of variables extracted from gaze analysis from toddlers using eye-tracking devices. The different videos try to capture social engagement, social information gathering gaze exchanges, and gaze following. We used the data to make a thorough comparison of machine learning algorithms (nine learning schemes), including some that were used in related prior research, and others that are popular in classification problems. The results show that several of the tested algorithms provided notable performance. This work was partially funded by the Department of Science, Innovation and Universities (Spain) under the National Program for Research, Development, and Innovation (Project RTI2018-099235-B-I00) and by the Fundación Trapote (Ayuntamiento de Gijón) https://hdl.handle.net/10651/70462 https://dx.doi.org/10.1007/s11042-023-17694-8
title Towards an automatic early screening system for autism spectrum disorder in toddlers based on eye‑tracking
spellingShingle Towards an automatic early screening system for autism spectrum disorder in toddlers based on eye‑tracking
Fernández Lanvin, Daniel|||0000-0002-5666-9809
title_short Towards an automatic early screening system for autism spectrum disorder in toddlers based on eye‑tracking
title_full Towards an automatic early screening system for autism spectrum disorder in toddlers based on eye‑tracking
title_fullStr Towards an automatic early screening system for autism spectrum disorder in toddlers based on eye‑tracking
title_full_unstemmed Towards an automatic early screening system for autism spectrum disorder in toddlers based on eye‑tracking
title_sort Towards an automatic early screening system for autism spectrum disorder in toddlers based on eye‑tracking
author Fernández Lanvin, Daniel|||0000-0002-5666-9809
author_facet Fernández Lanvin, Daniel|||0000-0002-5666-9809
González Rodríguez, Bernardo Martín|||0000-0002-9695-3919
Andrés Suárez, Javier|||0000-0001-6887-4087
Camero, Raquel
author_role author
author2 González Rodríguez, Bernardo Martín|||0000-0002-9695-3919
Andrés Suárez, Javier|||0000-0001-6887-4087
Camero, Raquel
author2_role author
author
author
description According to official estimations, autism spectrum disorder (ASD) affects around 1% of European newborns. The high level of dependency of ASD-affected subjects entails an extremely high social and economic cost. However, early intervention can drastically improve children’s development and thus reduce their dependency. One of the main common characteristics of subjects with ASD is difficulties with social interaction, which determines how they react to certain stimuli. This behavior can be automatically detected by analyzing their gaze. This study explores and evaluates the feasibility of automatic screening for ASD in toddlers under 24 months of age based on this specific behavior. We applied a matched pairs experimental design and a set of test videos, using a set of variables extracted from gaze analysis from toddlers using eye-tracking devices. The different videos try to capture social engagement, social information gathering gaze exchanges, and gaze following. We used the data to make a thorough comparison of machine learning algorithms (nine learning schemes), including some that were used in related prior research, and others that are popular in classification problems. The results show that several of the tested algorithms provided notable performance.
publishDate 2023
format article
url https://hdl.handle.net/10651/70462
https://dx.doi.org/10.1007/s11042-023-17694-8
language eng
eu_rights_str_mv openAccess
institution Universidad de Oviedo (UNIOVI)
collection RUO. Repositorio Institucional de la Universidad de Oviedo
reponame_str RUO. Repositorio Institucional de la Universidad de Oviedo
instname_str Universidad de Oviedo (UNIOVI)
_version_ 1878433905796710400
publishDateSort 2023
author_browse Andrés Suárez, Javier|||0000-0001-6887-4087
Camero, Raquel
Fernández Lanvin, Daniel|||0000-0002-5666-9809
González Rodríguez, Bernardo Martín|||0000-0002-9695-3919
score 6,9303427

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