Autism emotion interactive learning

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by difficulties in social communication, particularly in recognizing and interpreting facial expressions. Traditional methods for teaching emotional recognition, such as self reporting and physiological measurements, often lack engagement and practicality for children with ASD. This project addresses these limitations by developing an interactive app designed to enhance the social and emotional skills of children with ASD. The primary objectives of this project are to study the requirements for recognizing and learning emotion expressions in children with autism, design and develop an interactive emotion app tailored to these needs, and to validate the system's ability to recognize emotions such as Angry, Happy, Sad, Surprise, and Neutral. The app comprises three key modules: the Learn Module, offering educational content on emotions; the Activity Module, providing interactive games and exercises to reinforce learning; and the Scan Module, using real-time facial emotion detection with advanced computer vision and machine learning techniques, including convolutional neural networks (CNNs) and cascade classifiers for face detection. The app's interactivity is designed to be engaging and user-friendly for children with ASD. The validation process involves questionnaires and surveys administered to children at Sekolah Taman Universiti 1, gathering valuable feedback on the app's interactivity and effectiveness. This feedback highlights how well the app facilitates learning and engagement, providing insights into its impact on users' emotional and social development. The findings from the validation indicate that the app successfully enhances emotional recognition skills and provides an engaging learning experience for children with ASD.