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Q-CHAT-NAO: A robotic approach to autism screening in toddlers

, Rafael Martínez-Tomás, Pilar Pozo, Félix de la Paz, Encarnación Sarriá
Published: 1 June 2021
Journal of Biomedical Informatics , Volume 118; doi:10.1016/j.jbi.2021.103797

Abstract: The use of humanoid robots as assistants in therapy processes is not new. Several projects in the past several years have achieved promising results when combining human–robot interaction with standard techniques. Moreover, there are multiple screening systems for autism; one of the most used systems is the Quantitative Checklist for Autism in Toddlers (Q-CHAT-10), which includes ten questions to be answered by the parents or caregivers of a child. We present Q-CHAT-NAO, an observation-based autism screening system supported by a NAO robot. It includes the six questions of the Q-CHAT-10 that can be adapted to work in a robotic context; unlike the original system, it obtains information from the toddler instead of from an indirect source. The detection results obtained after applying machine learning models to the six questions in the Autistic Spectrum Disorder Screening Data for Toddlers dataset were almost equivalent to those of the original version with ten questions. These findings indicate that the Q-CHAT-NAO could be a screening option that would exploit all the benefits related to human-robot interaction.
Keywords: Autism spectrum disorder / Machine learning / Human-robot interaction

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