Abstract
It is evident that recently reported robot-assisted therapy systems for assessment of children with autism spectrum disorder (ASD) lack autonomous interaction abilities and require significant human resources. This paper proposes a sensing system that automatically extracts and fuses sensory features such as body motion features, facial expressions, and gaze features, further assessing the children behaviours by mapping them to therapist specified behavioural classes. Experimental results show that the developed system has a capability of interpreting characteristic data of children with ASD, thus has the potential to increase the autonomy of robots under the supervision of a therapist and enhance the quality of the digital description of children with ASD. The research outcomes pave the way to a feasible machine-assisted system for their behaviour assessment.
Original language | English |
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Article number | 18394336 |
Pages (from-to) | 1508-1518 |
Number of pages | 11 |
Journal | IEEE Sensors Journal |
Volume | 19 |
Issue number | 4 |
Early online date | 23 Oct 2018 |
DOIs | |
Publication status | Published - 15 Feb 2019 |
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The DREAM Dataset: Behavioural data from robot enhanced therapies for children with autism spectrum disorder
Billing, E. (Creator), School Of Engineering, C. A. M. (Contributor), Department Of Clinical Psychology And Psychotherapy, U. B. (Contributor), School Of Computing, U. O. P. (Contributor), Department Of Mechanical Engineering, V. U. B. (Contributor) & Robotics, S. (Contributor), University of Skövde, 23 Jul 2020
DOI: 10.5878/17p8-6k13, https://snd.gu.se/catalogue/dataset/snd1156-1/1
Dataset