Chevalier, P;
Li, JJ;
Ainger, E;
Alcorn, AM;
Babovic, S;
Charisi, V;
Petrovic, S;
... Evers, V; + view all
(2017)
Dialogue Design for a Robot-Based Face-Mirroring Game to Engage Autistic Children with Emotional Expressions.
In: Kheddar, A and Yoshida, E and Ge, SS and Suzuki, K and Cabibihan, J-J and Eyssel, F and He, H, (eds.)
Social Robotics. ICSR 2017. Lecture Notes in Computer Science.
(pp. pp. 546-555).
Springer: Cham, Switzerland.
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Abstract
We present design strategies for Human Robot Interaction for school-aged autistic children with limited receptive language. Applying these strategies to the DE-ENIGMA project (large EU project addressing emotion recognition in autistic children) supported development of a new activity for in facial expression imitation whereby the robot imitates the child’s face to encourage the child to notice facial expressions in a play-based game. A usability case study with 15 typically-developing children aged 4–6 at an English-language school in the Netherlands was performed to observe the feasibility of the setup and make design revisions before exposing the robot to autistic children.
Type: | Proceedings paper |
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Title: | Dialogue Design for a Robot-Based Face-Mirroring Game to Engage Autistic Children with Emotional Expressions |
ISBN-13: | 9783319700212 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1007/978-3-319-70022-9_54 |
Publisher version: | http://doi.org/10.1007/978-3-319-70022-9_54 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Robot, Child, Interaction, Prototype, Design, Mirroring, Imitation,Autism. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Social Research Institute |
URI: | https://discovery.ucl.ac.uk/id/eprint/10040012 |
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