Soleiman, Pegah and Moradi, Hadi and Mehralizadeh, Bijan and Ameri, Hamed and Arriaga, Rosa I. and Pouretemad, Hamid Reza and Baghbanzadeh, Negin and Vahid, Leila Kashani (2023) Fully robotic social environment for teaching and practicing affective interaction: Case of teaching emotion recognition skills to children with autism spectrum disorder, a pilot study. Frontiers in Robotics and AI, 10. ISSN 2296-9144
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Abstract
21st century brought along a considerable decrease in social interactions, due to the newly emerged lifestyle around the world, which became more noticeable recently of the COVID-19 pandemic. On the other hand, children with autism spectrum disorder have further complications regarding their social interactions with other humans. In this paper, a fully Robotic Social Environment (RSE), designed to simulate the needed social environment for children, especially those with autism is described. An RSE can be used to simulate many social situations, such as affective interpersonal interactions, in which observational learning can take place. In order to investigate the effectiveness of the proposed RSE, it has been tested on a group of children with autism, who had difficulties in emotion recognition, which in turn, can influence social interaction. An A-B-A single case study was designed to show how RSE can help children with autism recognize four basic facial expressions, i.e., happiness, sadness, anger, and fear, through observing the social interactions of two robots speaking about these facial expressions. The results showed that the emotion recognition skills of the participating children were improved. Furthermore, the results showed that the children could maintain and generalize their emotion recognition skills after the intervention period. In conclusion, the study shows that the proposed RSE, along with other rehabilitation methods, can be effective in improving the emotion recognition skills of children with autism and preparing them to enter human social environments.
Item Type: | Article |
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Subjects: | Universal Eprints > Engineering |
Depositing User: | Managing Editor |
Date Deposited: | 16 Jun 2023 03:26 |
Last Modified: | 30 Oct 2023 04:28 |
URI: | http://journal.article2publish.com/id/eprint/2168 |