Attention shifting during child—robot interaction: a preliminary clinical study for children with autism spectrum disorder
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There is an increasing need to introduce socially interactive robots as a means of assistance in autism spectrum disorder (ASD) treatment and rehabilitation, to improve the effectiveness of rehabilitation training and the diversification of treatment, and to alleviate the shortage of medical personnel in mainland China and other places in the world. In this preliminary clinical study, three different socially interactive robots with different appearances and functionalities were tested in therapy-like settings in four different rehabilitation facilities/institutions in Shenzhen, China. Seventy-four participants, including 52 children with ASD, whose processes of interacting with robots were recorded by three different cameras, all received a single-session three-robot intervention. Data were collected from not only the videos recorded, but also the questionnaires filled mostly by parents of the participants. Some insights from the preliminary results were obtained. These can contribute to the research on physical robot design and evaluations on robots in therapy-like settings. First, when doing physical robot design, some preferential focus should be on aspects of appearances and functionalities. Second, attention analysis using algorithms such as estimation of the directions of gaze and head posture of a child in the video clips can be adopted to quantitatively measure the prosocial behaviors and actions (e.g., attention shifting from one particular robot to other robots) of the children. Third, observing and calculating the frequency of the time children spend on exploring/playing with the robots in the video clips can be adopted to qualitatively analyze such behaviors and actions. Limitations of the present study are also presented.
Key wordsHuman-robot interaction Robot-enhanced therapy Socially interactive robots Robot-mediated intervention
CLC numberTP242.6 R748
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We thank the four rehabilitation facilities/institutions and their healthcare professionals for providing facilitation and assistance to our facilitators in this preliminary clinical study. We thank all the parents who took their children to participate in our study and supported us in many ways. We thank our guest students Shen-hong CHEN, Xiao-hong CAI, Hao-bo WANG, and Li-ping LI for their hard work in preparing and conducting this preliminary clinical study.
- Baltrušaitis T, Robinson P, Morency LP, 2016. OpenFace: an open source facial behavior analysis toolkit. Proc IEEE Winter Conf on Applications of Computer Vision, p.1–10. https://doi.org/10.1109/WACV.2016.7477553
- Clabaugh C, Becerra D, Deng E, et al., 2018. Month-long, in-home case study of a socially assistive robot for children with autism spectrum disorder. Companion of the ACM/IEEE Int Conf on Human-Robot Interaction, p.87–88. https://doi.org/10.1145/3173386.3177018
- Coeckelbergh M, Pop C, Simut R, et al., 2016. A survey of expectations about the role of robots in robot-assisted therapy for children with ASD: ethical acceptability, trust, sociability, appearance, and attachment. Sci Eng Ethics, 22(1):47–65. https://doi.org/10.1007/s11948-015-9649-x CrossRefGoogle Scholar
- English BA, Coates A, Howard A, 2017. Recognition of gestural behaviors expressed by humanoid robotic platforms for teaching affect recognition to children with autism—a healthy subjects pilot study. In: Kheddar A, Yoshida E, Ge SS, et al. (Eds.), Social Robotics. Springer, Cham. https://doi.org/10.1007/978-3-319-70022-9_56 Google Scholar
- Greczek J, Matarić M, 2015. Encouraging user autonomy through robot-mediated intervention. Proc 10th ACM/IEEE Int Conf on Human-Robot Interaction Extended, p.189–190. https://doi.org/10.1145/2701973.2702714
- Lee B, Xu J, Howard A, 2017. Does appearance matter? Validating engagement in therapy protocols with socially interactive humanoid robots. Proc IEEE Symp Series on Computational Intelligence, p.1–6. https://doi.org/10.1109/SSCI.2017.8285303
- Matarić MJ, 2017. Socially assistive robotics: human augmentation versus automation. Sci Rob, 2(4), Article eaam5410. https://doi.org/10.1126/scirobotics.aam5410
- Munir KM, Lavelle TA, Helm DT, et al., 2016. Autism: a global framework for action. https://doi.org/www.wish.org.qa/summits/wish-2016/forum-reports/
- Scassellati B, Admoni H, Matarić M, 2012. Robots for use in autism research. Ann Rev Biom Eng, 14:275–294. https://doi.org/10.1146/annurev-bioeng-071811-150036 CrossRefGoogle Scholar
- Simut R, van de Perre G, Costescu C, et al., 2016. Probogotchi: a novel edutainment device as a bridge for interaction between a child with ASD and the typically developed sibling. J Evid Based Psychot, 16(1):91–112.Google Scholar
- Sun X, Allison C, Matthews FE, et al., 2013. Prevalence of autism in mainland China, Hong Kong and Taiwan: a systematic review and meta-analysis. Mol Autism, 4(1), Article 7. https://doi.org/10.1186/2040-2392-4-7
- WUCAILU ASD Research Institute, 2017. Report on the Industry Development of Autism Education and Rehabilitation in China (II). Huaxia Publishing House, Beijing, China (in Chinese).Google Scholar
- Zheng ZW, 2017. The Situation of the Life and the Learning of Two Million Autistic Children Became Severe. Modern Education News, Mar. 31, 2017 (in Chinese).Google Scholar