The Quantitative Case-by-Case Analyses of the Socio-Emotional Outcomes of Children with ASD in Robot-Assisted Autism Therapy

Zhansaule Telisheva, Aida Amirova, Nazerke Rakhymbayeva, Aida Zhanatkyzy, Anara Sandygulova

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

With its focus on robot-assisted autism therapy, this paper presents case-by-case analyses of socio-emotional outcomes of 34 children aged 3–12 years old, with different cases of Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). We grouped children by the following characteristics: ASD alone (n = 22), ASD+ADHD (n = 12), verbal (n = 11), non-verbal (n = 23), low-functioning autism (n = 24), and high-functioning autism (n = 10). This paper provides a series of separate quantitative analyses across the first and last sessions, adaptive and non-adaptive sessions, and parent and no-parent sessions, to present child experiences with the NAO robot, during play-based activities. The results suggest that robots are able to interact with children in social ways and influence their social behaviors over time. Each child with ASD is a unique case and needs an individualized approach to practice and learn social skills with the robot. We, finally, present specific child–robot intricacies that affect how children engage and learn over time as well as across different sessions.

Original languageEnglish
Article number46
JournalMultimodal Technologies and Interaction
Volume6
Issue number6
DOIs
Publication statusPublished - Jun 2022

Keywords

  • adaptivity
  • ASD
  • individual differences
  • parental presence
  • robot-mediated therapy

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Human-Computer Interaction
  • Computer Science Applications
  • Computer Networks and Communications

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