Sensing-enhanced therapy system for assessing children with autism spectrum disorders: a feasibility study

Haibin Cai; Yinfeng Fang; Zhaojie Ju; Cristina Costescu; Daniel David; Erik Billing; Tom Ziemke; Serge Thill; Tony Belpaeme; Bram Vanderborght; David Vernon; Kathleen Richardson; Honghai Liu

doi:10.1109/JSEN.2018.2877662

Sensing-enhanced therapy system for assessing children with autism spectrum disorders: a feasibility study

Haibin Cai, Yinfeng Fang, Zhaojie Ju, Cristina Costescu, Daniel David, Erik Billing, Tom Ziemke, Serge Thill, Tony Belpaeme, Bram Vanderborght, David Vernon, Kathleen Richardson, Honghai Liu

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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
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	https://doi.org/10.1109/JSEN.2018.2877662
Publication status	Published - 15 Feb 2019

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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.",

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AU - Cai, Haibin

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AU - David, Daniel

AU - Billing, Erik

AU - Ziemke, Tom

AU - Thill, Serge

AU - Belpaeme, Tony

AU - Vanderborght, Bram

AU - Vernon, David

AU - Richardson, Kathleen

AU - Liu, Honghai

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Sensing-enhanced therapy system for assessing children with autism spectrum disorders: a feasibility study

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