Evaluation of a robot-assisted therapy for children with autism and intellectual disability

CONTI, Daniela, TRUBIA, Grazia, BUONO, Serafino, DI NUOVO, Santo and DI NUOVO, Alessandro (2018). Evaluation of a robot-assisted therapy for children with autism and intellectual disability. In: GIULIANI, Manuel, ASSAF, Tareq and GIANNACCINI, Maria Elena, (eds.) Towards autonomous robotic systems : 19th Annual Conference, TAROS 2018, Bristol, UK July 25-27, 2018, Proceedings. Lecture notes in computer science, 10965 . Cham, Springer, 405-415.

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Link to published version:: https://doi.org/10.1007/978-3-319-96728-8_34
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    Abstract

    It is well established that robots can be suitable assistants in the care and treatment of children with Autism Spectrum Disorder (ASD). However, the majority of the research focuses on stand-alone interventions, high-functioning individuals and the success is evaluated via qualitative analysis of videos recorded during the interaction. In this paper, we present a preliminary evaluation of our on-going research on integrating robot-assisted therapy in the treatment of children with ASD and Intellectual Disability (ID), which is the most common case. The experiment described here integrates a robot-assisted imitation training in the standard treat‐ ment of six hospitalised children with various level of ID, who were engaged by a robot on imitative tasks and their progress assessed via a quantitative psycho- diagnostic tool. Results show success in the training and encourage the use of a robotic assistant in the care of children with ASD and ID with the exception of those with profound ID, who may need a different approach.

    Item Type: Book Section
    Additional Information: ISSN: 0302-9743
    Uncontrolled Keywords: Autism spectrum disorder · Intellectual disability Socially assistive robotics · TEACCH · VB-MAPP
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Materials and Engineering Research Institute > Centre for Automation and Robotics Research > Sheaf Solutions
    Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
    Identification Number: https://doi.org/10.1007/978-3-319-96728-8_34
    Page Range: 405-415
    Depositing User: Daniela Conti
    Date Deposited: 01 Aug 2018 11:56
    Last Modified: 16 Nov 2018 14:03
    URI: http://shura.shu.ac.uk/id/eprint/22141

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