TY - JOUR
T1 - Sensing-enhanced therapy system for assessing children with autism spectrum disorders: a feasibility study
AU - Cai, Haibin
AU - Fang, Yinfeng
AU - Ju, Zhaojie
AU - Costescu, Cristina
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
PY - 2019/2/15
Y1 - 2019/2/15
N2 - 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.
AB - 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.
U2 - 10.1109/JSEN.2018.2877662
DO - 10.1109/JSEN.2018.2877662
M3 - Article
VL - 19
SP - 1508
EP - 1518
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
SN - 1530-437X
IS - 4
M1 - 18394336
ER -