• Maria Eleonora Minissi, Alberto Altozano, Javier Marin-Morales, Neus Centelles, Marian Sirera, Luis Abad, and Mariano Alcañiz.
• Instituto Universitario de Investigación en Tecnología Centrada en el Ser Humano (HUMAN-tech), Universitat Politécnica de Valencia, Valencia, España.
• Medicina (B Aires). 2024 Mar 1; 84 Suppl 1: 576457-64.

IntroductionAutism Spectrum Disorder (ASD) is a neurodevelopmental condition which traditional assessment procedures encounter certain limitations. The current ASD research field is exploring and endorsing innovative methods to assess the disorder early on, based on the automatic detection of biomarkers. However, many of these procedures lack ecological validity in their measurements. In this context, virtual reality (VR) shows promise for objectively recording biosignals while users experience ecological situations.MethodsThis study outlines a novel and playful VR procedure for the early assessment of ASD, relying on multimodal biosignal recording. During a VR experience featuring 12 virtual scenes, eye gaze, motor skills, electrodermal activity and behavioural performance were measured in 39 children with ASD and 42 control peers. Machine learning models were developed to identify digital biomarkers and classify autism.ResultsBiosignals reported varied performance in detecting ASD, while the combined model resulting from the combination of specific-biosignal models demonstrated the ability to identify ASD with an accuracy of 83% (SD = 3%) and an AUC of 0.91 (SD = 0.04).DiscussionThis screening tool may support ASD diagnosis by reinforcing the outcomes of traditional assessment procedures.

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