Background Individuals with autism spectrum disorder (ASD) exhibit frequent behavioral deficits in facial emotion recognition (FER). It remains unknown whether these deficits arise because facial emotion information is not encoded in their neural signal or because it is encodes but fails to translate to FER behavior (deployment). This distinction has functional implications, including constraining when differences in social information processing occur in ASD, and guiding interventions (i.e., developing prosthetic FER vs. reinforcing existing skills). Methods We utilized a discriminative and contemporary machine learning approach—deep convolutional neural networks—to classify facial emotions viewed by individuals with and without ASD (N = 88) from concurrently recorded electroencephalography signals. Results The convolutional neural

Children with Autism Spectrum Disorder present several difficulties in social interaction, communication obstaclesand restricted and repeated behaviors. Social connection with others is typically challenging for them, and they are frequentlyunsure of how to react to other people’s emotions, facial expressions, and movements of their body, and especially of how torespond to various social circumstances. Recent review studies regarding VR for children with ASD have found that most ofthe relevant interventions aimed at improving social and emotional skills, as well as common activities of everyday life. In thiswork, we are going to present studies of the most current applications of VR

Autism Spectrum Disorder is a neurological and developmental disorder. Children diagnosed with this disorder have persistent deficits in their social-emotional reciprocity skills, nonverbal communication, and developing, maintaining, and understanding relationships. Besides, autistic children usually have motor deficits that influence their imitation and gesture production ability. The present study aims to review and analyze the current research findings in using robot-based and virtual reality-based intervention to support the therapy of improving the social, communication, emotional, and academic deficits of children with autism. Experimental data from the surveyed works are analyzed regarding the target behaviors and how each technology, robot, or virtual