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How An Automated Gesture Imitation Game Can Improve Social Interactions With Teenagers With ASD

Abstract : With the outlook of improving communication and social abilities of people with ASD, we propose to extend the paradigm of robot-based imitation games to ASD teenagers. In this paper, we present an interaction scenario adapted to ASD teenagers, propose a computational architecture using the latest machine learning algorithm Openpose for human pose detection, and present the results of our basic testing of the scenario with human caregivers. These results are preliminary due to the number of session (1) and participants (4). They include a technical assessment of the performance of Openpose, as well as a preliminary user study to confirm our game scenario could elicit the expected response from subjects.
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https://hal-imt-atlantique.archives-ouvertes.fr/hal-02894330
Contributor : Sao Mai Nguyen <>
Submitted on : Friday, July 10, 2020 - 3:33:02 PM
Last modification on : Wednesday, October 14, 2020 - 9:28:04 AM

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  • HAL Id : hal-02894330, version 1
  • ARXIV : 2007.05394

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Linda Nanan Vallée, Sao Mai Nguyen, Christophe Lohr, Ioannis Kanellos, Olivier Asseu. How An Automated Gesture Imitation Game Can Improve Social Interactions With Teenagers With ASD. IEEE ICRA Workshop on Social Robotics for Neurodevelopmental Disorders, Jun 2020, Paris, France. ⟨hal-02894330⟩

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