How An Automated Gesture Imitation Game Can Improve Social Interactions With Teenagers With ASD
July 10, 2020 Β· Declared Dead Β· π IEEE International Conference on Robotics and Automation
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Authors
Linda Nanan VallΓ©e, Sao Mai Nguyen, Christophe Lohr, Ioannis Kanellos, Olivier Asseu
arXiv ID
2007.05394
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CY,
cs.LG,
cs.RO,
stat.ML
Citations
1
Venue
IEEE International Conference on Robotics and Automation
Last Checked
4 months ago
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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