Analysis of softwares for emotion recognition in children and teenagers with autism spectrum disorder

ABSTRACT

ABSTRACT Purpose: to investigate the use of softwares for emotion recognition in children and teenagers with Autism Spectrum Disorders (ASD). Methods: an integrative review of the literature with scientific papers published from 2012 to 2017 indexed in Periódico Capes, Science Direct, and PudMed; combined descriptors autism AND emotion AND software; autism AND emotion recognition AND software. Inclusion criterion was the use of software related to emotion recognition in children and teenagers with ASD, up to 18 years old. Review papers and those using robots were excluded. Results: ten international papers were reviewed. The most used emotional expressions were "happiness", "fear", "anger", "disgust", "sadness", and "surprise". Ten software programs were described Emotion Recognition Task (1), Cambridge Mindreading Face-Voice Battery for Children (3), Mind Reading (2), Mood Maker (1), Virtual-Reality Emotion Sensitivity Test (1), FaceSay (1), Penn Emotion Recognition (1), FaceMaze Game (1), Computer Emotion Recognition Toolbox (CERT) (1), and Emotiplay (1). Conclusion: studies with software programs focused on ASD intervention allow future research efforts in the diagnosis and intervention of this disorder.