ASD Screening for Toddlers via Physical Interpretation through Advanced AI

Abstract

Autism Spectrum Disorders (ASD) are generally causing challenges for significant communication, social interaction, and behavioral patterns to elderly people and children. Providing early treatments can make a huge advancement in the lives of children. Meanwhile, there is a limited number of systems to screen and identify ASD children. This research project is about developing a set of tools bonding together to one system called "AI - Bot Simon" to screen kids with ASD by filling the gap. In the system development process mainly, Audio, Facial expressions, Gestures, and the Gates of a targeted group of children are considered for screening. Since the target group is 6 months to 4 years, they are in early language development age. On the technical side of view Machine Learning (ML) and Deep Learning (DL) with Neural Networks (NN) are used for advanced screening and monitoring for automation of the process. In the last step of the development, all the outputs or information gathered from each tool or model, processed, analyzed, and provided to the users of the system by an Artificial Intelligence (AI) bot implemented with a web application and a mobile application whether children are suffering from ASD or not.