Seeing through a robot's eyes: A cross‐sectional exploratory study in developing a robotic screening technology for autism
Wing‐Chee So, Elsa Wong, Wingo Ng, John Fuego, Sally Lay, Ming‐Ting So, Yuen‐Yung Lee, Wai‐Yan Chan, Lok‐Ying Chua, Hiu‐Lok Lam, Wing‐Tung Lam, H. H. S. Li, Wing‐To Leung, Yu‐Hei Ng, Wing‐Ting Wong
- Year
- 2024
- Citations
- 4
- Access
- Open access
Abstract
The present exploratory cross-sectional case-control study sought to develop a reliable and scalable screening tool for autism using a social robot. The robot HUMANE, installed with computer vision and linked with recognition technology, detected the direction of eye gaze of children. Children aged 3-8 (M = 5.52; N = 199) participated, 87 of whom had been confirmed with autism, 55 of whom were suspected to have autism, and 57 of whom were not considered to cause any concern for having autism. Before a session, a human experimenter instructed HUMANE to narrate a story to a child. HUMANE prompted the child to return his/her eye gaze to the robot if the child looked away, and praised the child when it re-established its eye gaze quickly after a prompt. The reliability of eye gaze detection was checked across all pairs of human raters and HUMANE and reached 0.90, indicating excellent interrater agreement. Using the pre-specified reference standard (Autism Spectrum Quotient), the sensitivity and specificity of the index tests (i.e., the number of robot prompts and duration of inattentiveness) reached 0.88 or above and the Diagnostic Odds Ratios were beyond 190. These results show that social robots may detect atypical eye patterns, suggesting a potential future for screening autism using social robots.
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