How are you feeling? Design and testing emotional dictionary for NAO robot to be used with children

This paper presents the development and
preliminary evaluation of an emotional dictionary for the NAO
humanoid robot, to be used in games activities with children with
Autism Spectrum Disorder (ASD). The emotional dictionary
integrates multimodal elements, such as gestures, LED eye
colours, and speech, to enable the robot to convey positive and
negative emotional states during interactive game scenarios.
These scenarios are designed to support the development of social
and cognitive skills in children with ASD. To create the emotional
dictionary, eight gestures (four positive and four negative) were
identified from existing literature and refined through an
iterative co-design process involving psychologists, therapists,
and engineers. The emotional expressions were further enhanced
using eye colour changes (yellow/orange for positive, blue/violet
for negative) and context-specific verbal feedback. A preliminary
evaluation was conducted with 34 healthy young adults to
validate the ability of the robot to correctly elicit emotions.
Participants rated the robot’s emotional expressions based on
valence and identified in emotional categories. The results
demonstrated high recognition accuracy for both positive (e.g.,
happiness) and negative (e.g., sadness) combinations, with
valence ratings distinctly separating these emotional states. These
preliminary results provide guidelines on which combinations are
most suitable to be used as feedback in games activities. Future
work will incorporate these combinations into interactive game
dynamics and extend testing to both typical and atypical children.