Abstract

Recent technological advancements have given rise to automatic emotion recognition technologies, which hold potential in supporting children with autism to better comprehend and respond to emotions. Automatic emotion recognition involves using algorithms and machine learning techniques to automatically detect and classify emotions from various sources, such as facial expressions, speech, physiological signals, and more. These technologies offer a non-intrusive and objective way to assess and monitor emotions, which can be particularly beneficial for children with autism who may have difficulty verbalizing their feelings. The objective of this review article is to present a comprehensive overview of the current state-of-the-art in automatic emotion recognition technologies applied to children with autism. It explores relevant studies, methodologies, findings, challenges, and future directions within this evolving research field.