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      Smiles as a Signal of Prosocial Behaviors Toward the Robot in the Therapeutic Setting for Children With Autism Spectrum Disorder

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          Abstract

          We explored how robot-assisted therapy based on smile analysis may facilitate the prosocial behaviors of children with autism spectrum disorder. Prosocial behaviors, which are actions for the benefit of others, are required to belong to society and increase the quality of life. As smiling is a candidate for predicting prosocial behaviors in robot-assisted therapy, we measured smiles by annotating behaviors that were recorded with video cameras and by classifying facial muscle activities recorded with a wearable device. While interacting with a robot, the participants experienced two situations where participants' prosocial behaviors are expected, which were supporting the robot to walk and helping the robot from falling. We first explored the overall smiles at specific timings and prosocial behaviors. Then, we explored the smiles triggered by a robot and behavior changes before engaging in prosocial behaviors. The results show that the specific timing of smiles and prosocial behaviors increased in the second session of children with autism spectrum disorder. Additionally, a smile was followed by a series of behaviors before prosocial behavior. With a proposed Bayesian model, smiling, or heading predicted prosocial behaviors with higher accuracy compared to other variables. Particularly, voluntary prosocial behaviors were observed after smiling. The findings of this exploratory study imply that smiles might be a signal of prosocial behaviors. We also suggest a probabilistic model for predicting prosocial behaviors based on smile analysis, which could be applied to personalized robot-assisted therapy by controlling a robot's movements to arouse smiles and increase the probability that a child with autism spectrum disorder will engage in prosocial behaviors.

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          Most cited references 60

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          Diagnostic and Statistical Manual of Mental Disorders

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                Author and article information

                Contributors
                Journal
                Front Robot AI
                Front Robot AI
                Front. Robot. AI
                Frontiers in Robotics and AI
                Frontiers Media S.A.
                2296-9144
                26 May 2021
                2021
                : 8
                Affiliations
                1Faculty of Engineering, Information and Systems, University of Tsukuba , Tsukuba, Japan
                2Faculty of Human Sciences, University of Tsukuba , Tsukuba, Japan
                3Faculty of Sport Science, Nippon Sport Science University , Yokohama, Japan
                Author notes

                Edited by: Andreas Riener, Technische Hochschule Ingolstadt, Germany

                Reviewed by: Levern Currie, Virginia Tech, United States; Myounghoon Jeon, Virginia Tech, United States

                *Correspondence: SunKyoung Kim kim@ 123456ai.iit.tsukuba.ac.jp

                This article was submitted to Human-Robot Interaction, a section of the journal Frontiers in Robotics and AI

                Article
                10.3389/frobt.2021.599755
                8187796
                bc0f216a-dea5-4c97-8186-68d4e2093e18
                Copyright © 2021 Kim, Hirokawa, Matsuda, Funahashi and Suzuki.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Page count
                Figures: 10, Tables: 4, Equations: 3, References: 60, Pages: 16, Words: 11135
                Funding
                Funded by: Core Research for Evolutional Science and Technology 10.13039/501100003382
                Funded by: Japan Society for the Promotion of Science 10.13039/501100001691
                Award ID: JP20J11008
                Categories
                Robotics and AI
                Original Research

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