Back to Search Start Over

"I See What You Feel": An Exploratory Study to Investigate the Understanding of Robot Emotions in Deaf Children.

Authors :
Cirasa, Carla
Høgsdal, Helene
Conti, Daniela
Source :
Applied Sciences (2076-3417); Feb2024, Vol. 14 Issue 4, p1446, 14p
Publication Year :
2024

Abstract

Research in the field of human–robot interactions (HRIs) has advanced significantly in recent years. Social humanoid robots have undergone severe testing and have been implemented in a variety of settings, for example, in educational institutions, healthcare facilities, and senior care centers. Humanoid robots have also been assessed across different population groups. However, research on various children groups is still scarce, especially among deaf children. This feasibility study explores the ability of both hearing and deaf children to interact with and recognize emotions expressed by NAO, the humanoid robot, without relying on sounds or speech. Initially, the children watched three video clips portraying emotions of happiness, sadness, and anger. Depending on the experimental condition, the children observed the humanoid robot respond to the emotions in the video clips in a congruent or incongruent manner before they were asked to recall which emotion the robot exhibited. The influence of empathy on the ability to recognize emotions was also investigated. The results revealed that there was no difference in the ability to recognize emotions between the two conditions (i.e., congruent and incongruent). Indeed, NAO responding with congruent emotions to video clips did not contribute to the children recognizing the emotion in NAO. Specifically, the ability to predict emotions in the video clips and gender (females) were identified as significant predictors to identify emotions in NAO. While no significant difference was identified between hearing and deaf children, this feasibility study aims to establish a foundation for future research on this important topic. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
4
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
175652434
Full Text :
https://doi.org/10.3390/app14041446