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. 2019 Jul 5:10:1503.
doi: 10.3389/fpsyg.2019.01503. eCollection 2019.

Interaction With Social Robots: Improving Gaze Toward Face but Not Necessarily Joint Attention in Children With Autism Spectrum Disorder

Wei Cao  1 , Wenxu Song  1 , Xinge Li  2 , Sixiao Zheng  3 , Ge Zhang  4 , Yanting Wu  2 , Sailing He  1 , Huilin Zhu  5 , Jiajia Chen  1   6
Affiliations

Interaction With Social Robots: Improving Gaze Toward Face but Not Necessarily Joint Attention in Children With Autism Spectrum Disorder

Wei Cao et al. Front Psychol. .

Abstract

It is widely recognized that robot-based interventions for autism spectrum disorders (ASD) hold promise, but the question remains as to whether social humanoid robots could facilitate joint attention performance in children with ASD. In this study, responsive joint attention was measured under two conditions in which different agents, a human and a robot, initiated joint attention via video. The participants were 15 children with ASD (mean age: 4.96 ± 1.10 years) and 15 typically developing (TD) children (mean age: 4.53 ± 0.90 years). In addition to analyses of fixation time and gaze transitions, a longest common subsequence approach (LCS) was employed to compare participants' eye movements to a predefined logical reference sequence. The fixation of TD toward agent's face was earlier and longer than children with ASD. Moreover, TD showed a greater number of gaze transitions between agent's face and target, and higher LCS scores than children with ASD. Both groups showed more interests in the robot's face, but the robot induced a lower proportion of fixation time on the target. Meanwhile participants showed similar gaze transitions and LCS results in both conditions, suggesting that they could follow the logic of the joint attention task induced by the robot as well as human. We have discussed the implications for the effects and applications of social humanoid robots in joint attention interventions.

Keywords: autism spectrum disorder; eye tracking; joint attention; longest common subsequence; social robot.

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Figures

FIGURE 1
FIGURE 1
Stills from the stimuli in (A–C) the robot condition, and (E–G) the human condition. (D,H) Indicate the areas of interest: the green area is the agent’s face, the yellow area is the agent’s body, the blue areas are the three objects (target and non-targets), the orange area is the picture frame (distractor), and the rest of the screen is the background. Written informed consent was obtained from the individual for the publication of this image.
FIGURE 2
FIGURE 2
The real-time gaze traces of two participants, one child with ASD (A,B) and one TD child (C,D) during the joint attention segment of videos in each condition (human condition: A,C; robot condition: B,D). Different areas of interest are represented on the y axis, and the x axis represents time. Black lines represent eye movement traces, where each point corresponds to a fixation in one area of interest recorded at a certain time point. Red circles indicate gaze transitions between the agent’s face and the target. Light red and light blue shaded areas cover the face and target regions, which are used in the reference sequences in LCS analysis; joint attention behavior can be observed in these areas.
FIGURE 3
FIGURE 3
(A) The latency (s) of participants’ first fixation on different areas of interest. (B) Results of post hoc analysis of the interaction between group and area of interest, indicating that the typically developing group looked at the face earlier than did the group with ASD, while the group with ASD looked at the background earlier than did the typically developing group. (C) The interaction between stimulus type and area of interest, demonstrating that all participants looked at the human body earlier than they looked at the robot body. ∗∗Means that the significant level is p < 0.01 and ∗ means p < 0.05.
FIGURE 4
FIGURE 4
(A) The percentage of fixation time spent on different areas of interest by participants with ASD and TD participants. (B) Results of post hoc analysis of the interaction between group and area of interest, indicating that the TD group fixated longer than the group with ASD on the agent’s face, whereas the ASD group looked for longer than the TD group at the picture frame and non-targets. (C) The interaction between stimulus type and area of interest, demonstrating that all participants spend more time looking at the face area in the robot condition (p = 0.038), and more time looking at the target and non-targets in the human condition. ∗∗Means that the significant level is p < 0.01 and ∗ means p < 0.05.
FIGURE 5
FIGURE 5
(A) The number of congruent and incongruent gaze transitions made by each participant group for each stimulus types. (B) Longest common subsequence (LCS) scores for each participant group and stimulus type.
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References

    1. American Psychiatric Association (2000). Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR). Washington, DC: American Psychiatric Press.
    1. American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental Disorders, 5th Edn. Washington, DC: American Psychiatric Press.
    1. Anzalone S. M., Tilmont E., Boucenna S., Xavier J., Jouen A.-L., Bodeau N., et al. (2014). How children with autism spectrum disorder behave and explore the 4-dimensional (spatial 3D + time) environment during a joint attention induction task with a robot. Res. Autism Spect. Dis. 8 814–826. 10.1016/j.rasd.2014.03.002 - DOI
    1. Bekele E., Crittendon J. A., Swanson A., Sarkar N., Warren Z. E. (2014). Pilot clinical application of an adaptive robotic system for young children with autism. Autism 18 598–608. 10.1177/1362361313479454 - DOI - PMC - PubMed
    1. Biao S., Xiaochun M. (1990). The revision of trail norm of peabody picture vocabulary test revised (PPVT-R) in shanghai proper. Inform. Psychol. Sci. 13 22–27.

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