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Eye Tracking Young Children with Autism
Published on: March 27, 2012
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Information and Communication Technologies to Support Early Screening of Autism Spectrum Disorder: A Systematic
Lorenzo Desideri1, Patricia Pérez-Fuster2, Gerardo Herrera2
1AIAS Bologna Onlus, 40134 Bologna, Italy.
Children (Basel, Switzerland)
|February 4, 2021
Summary
Recent digital technologies show promise for early autism spectrum disorder (ASD) detection in preschoolers. Further research is needed to integrate these tools into clinical practice for better outcomes.
Area of Science:
- Pediatric Neurology
- Developmental Psychology
- Human-Computer Interaction
Background:
- Early detection of autism spectrum disorder (ASD) is crucial for timely intervention and improved outcomes in young children.
- Digital technologies offer novel approaches for screening and assessment of developmental disorders.
- The COVID-19 pandemic highlighted the need for remote and accessible screening methods.
Purpose of the Study:
- To systematically review recent digital technologies for early autism spectrum disorder (ASD) detection in preschool children (up to six years).
- To assess the interface modalities and screening tool levels employed in technology-based ASD detection.
- To evaluate the potential of these technologies in supporting clinical practice for early ASD identification.
Main Methods:
- Systematic literature search across major databases (PubMed, PsycInfo, ERIC, etc.) up to January 2020, with a follow-up search until December 2020.
- Inclusion criteria applied to identify relevant English-language articles and conference papers.
- Analysis of 28 selected studies based on interface modalities (Natural User Interface, PC/mobile, Wearable, Robotics) and screening tool levels.
Main Results:
- Twenty-eight studies met inclusion criteria, utilizing diverse digital technologies for ASD detection.
- Natural User Interface (eye-trackers), PC/mobile, Wearable, and Robotics were the primary interface modalities.
- Most studies (n=20) employed Level 1 screening tools, indicating a focus on initial detection.
Conclusions:
- Digital technologies present promising tools for supporting early autism spectrum disorder (ASD) detection in preschool children.
- While psychometric data is encouraging, further research is essential to understand technology acceptability and adoption in clinical settings.
- Increased use rates of technology-based screenings can enhance early identification and intervention for ASD.
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