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‑trackingFernández Lanvin, Daniel|||0000-0002-5666-9809González Rodríguez, Bernardo Martín|||0000-0002-9695-3919Andrés Suárez, Javier|||0000-0001-6887-4087Camero, RaquelAccording 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)20232023-12-11journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articlehttps://hdl.handle.net/10651/70462https://dx.doi.org/10.1007/s11042-023-17694-8reponame:RUO. Repositorio Institucional de la Universidad de Oviedoinstname:Universidad de Oviedo (UNIOVI)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:digibuo.uniovi.es:10651/704622026-06-07T06:38:51Z
dc.title.none.fl_str_mv Towards an automatic early screening system for autism spectrum disorder in toddlers based on eye‑tracking
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
dc.creator.none.fl_str_mv 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 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
dc.date.none.fl_str_mv 2023
2023-12-11
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10651/70462
https://dx.doi.org/10.1007/s11042-023-17694-8
url https://hdl.handle.net/10651/70462
https://dx.doi.org/10.1007/s11042-023-17694-8
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:RUO. Repositorio Institucional de la Universidad de Oviedo
instname:Universidad de Oviedo (UNIOVI)
instname_str Universidad de Oviedo (UNIOVI)
reponame_str RUO. Repositorio Institucional de la Universidad de Oviedo
collection RUO. Repositorio Institucional de la Universidad de Oviedo
repository.name.fl_str_mv
repository.mail.fl_str_mv
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