Pinto-Bernal Maria J, Sierra M Sergio D, Munera Marcela, Casas Diego, Villa-Moreno Adriana, Frizera-Neto Anselmo, Stoelen Martin F, Belpaeme Tony, Cifuentes Carlos A
IDLab, Ghent University-imec, Ghent, Belgium.
Bristol Robotics Laboratory, University of the West of England, Bristol, United Kingdom.
Front Neurorobot. 2023 Mar 2;17:1044491. doi: 10.3389/fnbot.2023.1044491. eCollection 2023.
Socially Assistive Robotics has emerged as a potential tool for rehabilitating cognitive and developmental disorders in children with autism. Social robots found in the literature are often able to teach critical social skills, such as emotion recognition and physical interaction. Even though there are promising results in clinical studies, there is a lack of guidelines on selecting the appropriate robot and how to design and implement the child-robot interaction.
This work aims to evaluate the impacts of a social robot designed with three different appearances according to the results of a participatory design (PD) process with the community. A validation study in the emotion recognition task was carried out with 21 children with autism.
Spectrum disorder results showed that robot-like appearances reached a higher percentage of children's attention and that participants performed better when recognizing simple emotions, such as happiness and sadness.
This study offers empirical support for continuing research on using SAR to promote social interaction with children with ASD. Further long-term research will help to identify the differences between high and low-functioning children.
社交辅助机器人已成为治疗自闭症儿童认知和发育障碍的一种潜在工具。文献中发现的社交机器人通常能够教授关键的社交技能，如情感识别和身体互动。尽管临床研究取得了一些有前景的成果，但在选择合适的机器人以及如何设计和实施儿童与机器人的互动方面仍缺乏指导方针。
这项工作旨在根据与社区进行的参与式设计（PD）过程的结果，评估设计有三种不同外观的社交机器人的影响。对21名自闭症儿童进行了情感识别任务的验证研究。
谱系障碍结果表明，类机器人外观吸引儿童注意力的比例更高，并且参与者在识别简单情绪（如快乐和悲伤）时表现更好。
本研究为继续开展使用社交辅助机器人促进与自闭症谱系障碍儿童的社交互动的研究提供了实证支持。进一步的长期研究将有助于确定高功能和低功能儿童之间的差异。
