AutiScan: Screening of Autism Spectrum Disorder Specific to Indian Region

Abstract

Autism Spectrum Disorder (ASD) is a neurological condition that can affect a person's language development, speech, cognition, and social skills for the rest of their lives. Prevalence of ASD is about 1 in 100 children in India under the age of 10, and nearly 1 in 8 has at least one neurodevelopmental condition according to the 2011 Census [24]. Machine/Deep Learning methods have proven helpful in order to quickly and accurately determine the risk of ASD. Early intervention in the child's preschool and primary school years can aid in the development of important social, communicative, functional, and behavioral skills. It has been observed that very few studies and research has been done on ASD in India, which is our motivation to take this as our project. The very sparse number of current studies show that there is no existing dataset for children in India. In this paper, we intend to first understand what autism spectrum disorder is, the symptoms it presents itself in, currently available diagnosis tests, treatment options and how AI is relevant in this domain. Further, the idea would be to understand the extent of ASD study and research done in India. We have pioneered ASD Research in India as we formulated a dataset of Indian children to kickstart ASD research in India. Out of the three approaches we tried, the CNN-RNN Video Classification approach where the CNN block has a pretrained feature extractor (Inception V3) to classify whether a child has ASD or not performed with 98.48 % train and 90.48 % test accuracy. We have further explained the wide future scope this research inquiry has to offer. Our research intends to help establish the need for a population-specific study in the detection and diagnosis of ASD in Indian children.