Could Interaction with Social Robots Facilitate Joint Attention of Children with Autism Spectrum Disorder?

Wei Cao, Wenxu Song, Xinge Li, Sixiao Zheng, Ge Zhang, Yanting Wu, Sailing He, Huilin Zhu, Jiajia Chen

This research addressed whether interactions with social robots could facilitate joint attention of the autism spectrum disorder (ASD). Two conditions of initiators, namely 'Human' vs. 'Robot' were measured with 15 children with ASD and 15 age-matched typically developing (TD) children. Apart from fixation and gaze transition, a new longest common subsequence (LCS) approach was proposed to analyze eye-movement traces. Results revealed that children with ASD showed deficits of joint attention. Compared to the human agent, robot facilitate less fixations towards the targets, but it attracted more attention and allowed the children to show gaze transition and to follow joint attention logic. This results highlight both potential application of LCS analysis on eye-tracking studies and of social robot to intervention.

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