Using a social robot to teach gestural recognition and production in children with autism spectrum disorders

Abstract

While it has been argued that children with autism spectrum disorders are responsive to robot-like toys, very little research has examined the impact of robot-based intervention on gesture use. These children have delayed gestural development. We used a social robot in two phases to teach them to recognize and produce eight pantomime gestures that expressed feelings and needs. Compared to the children in the wait-list control group (N = 6), those in the intervention group (N = 7) were more likely to recognize gestures and to gesture accurately in trained and untrained scenarios. They also generalized the acquired recognition (but not production) skills to human-to-human interaction. The benefits and limitations of robot-based intervention for gestural learning were highlighted.

Implications for Rehabilitation

• Compared to typically-developing children, children with autism spectrum disorders have delayed development of gesture comprehension and production.

• Robot-based intervention program was developed to teach children with autism spectrum disorders recognition (Phase I) and production (Phase II) of eight pantomime gestures that expressed feelings and needs.

• Children in the intervention group (but not in the wait-list control group) were able to recognize more gestures in both trained and untrained scenarios and generalize the acquired gestural recognition skills to human-to-human interaction.

• Similar findings were reported for gestural production except that there was no strong evidence showing children in the intervention group could produce gestures accurately in human-to-human interaction.

Keywords:

• Robot-based intervention
• gestural training
• non-verbal communication
• randomized controlled trial
• low-functioning autism spectrum disorders
• Chinese-speaking children

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research has been fully supported by the grant from the Chinese University of Hong Kong (Project no. CUHK3230211).