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Sensing-enhanced therapy system for assessing children with autism spectrum disorders: A feasibility study
journal contribution
posted on 2019-10-09, 08:52 authored by Haibin CaiHaibin Cai, Yinfeng Fang, Zhaojie Ju, Cristina Costescu, Daniel David, Erik Billing, Tom Ziemke, Serge Thill, Tony Belpaeme, Bram Vanderborght, David Vernon, Kathleen Richardson, Honghai LiuIt 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 behaviors by mapping them to therapist-specified behavioral 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 behavior assessment.
Funding
EU Seventh Framework Program DREAM under Grant 611391
History
School
- Science
Department
- Computer Science
Published in
IEEE Sensors JournalVolume
19Issue
4Pages
1508 - 1518Publisher
IEEEVersion
- AM (Accepted Manuscript)
Rights holder
© IEEEPublisher statement
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Acceptance date
2018-10-11Publication date
2018-10-23Copyright date
2018ISSN
1530-437XeISSN
1558-1748Language
- en