AutisMitr: Emotion Recognition Assistive Tool for Autistic Children

Abstract

Assistive technology has proven to be one of the most significant inventions to aid people with Autism to improve the quality of their lives. In this study, a real-time emotion recognition system for autistic children has been developed. Emotion recognition is implemented by executing three stages: Face identification, Facial Feature extraction, and feature classification. The objective is to frame a system that includes all three stages of emotion recognition activity that executes expeditiously in real time. Thus, Affectiva SDK is implemented in the application. The propound system detects at most 7 facial emotions: anger, disgust, fear, joy, sadness, contempt, and surprise. The purpose for performing this study is to teach emotions to individuals suffering from autism, as they lack the ability to respond appropriately to others emotions. The proposed application was tested with a group of typical children aged 6–14 years, and positive outcomes were achieved.

English Flipped Classroom Teaching Mode Based on Emotion Recognition Technology

“…To avoid major differences in the cognition of the same emotion among the annotators, the annotators should conduct a trial operation on the trial sample before the formal annotation. They compare their scoring results with standard results to reduce the negative correlation of labeling results ( Singh and Dewan, 2020 ). The tagger first judges the basic emotion expressed by the image or audio.…”

Emotions Recognition in people with Autism using Facial Expressions and Machine Learning Techniques: Survey

“… [20] , In their paper, Face recognition, face feature extraction, and feature classification were the three steps that went into designing the real-time emotion detection system for autistic children that was developed as part of this study. The Proposed System can only identify seven distinct facial emotions, including anger, disgust, fear, joy, sadness, contempt, and surprise.…”

“…They may also have difficulty regulating their emotions, leading to intense or inappropriate emotional reactions in social situations [18]. Understanding the emotional state of people with ASD is essential for developing effective interventions to improve their social and emotional function [19] [20]. By utilizing methods based on facial expressions, we can gain a better understanding of the emotional experiences of people with ASD and develop strategies to help them manage their emotions effectively [21] [22].…”

The power of computer vision : a critital analysis

“…Microsoft's PeopleLens. See: Morrison et al, 2021); object and facial recognition could help people with dementia or memory loss by labeling objects and familiar faces for them (Munteanu et al, 2022); and emotion recognition could help those who struggle to read and respond to others' emotional expressions (Singh & Dewan, 2020).…”