Design and develop a website capable of predicting an ASD index for children living in underserved, underrepresented, and low-income communities, as well as providing users with the resources to evaluate their child for the potential need to seek a professional diagnosis.
iGAIT is not meant for diagnosing children's ASD but instead is intended as a platform for users across the world to receive a cost-effective approach to evaluating children for ASD as early as possible.
- 71,469 children in Illinois (1 in 44 children in the entire US) have autism spectrum disorder (CDC)
- Because of poor healthcare or high costs, children from minority, low-income, and rural backgrounds are often diagnosed at a late age
- Gender, age, and cultural disparities in diagnosis also exist - leaving a large portion of children undiagnosed (review)
- Due to the complex and spectromic nature of ASD, it is difficult to recognize and diagnose
- Dr. Ziteng Wang, Department of Industrial and Systems Engineering, College of Engineering & Engineering Technology, Northern Illinois University
- John White, Department of Computer Science, Department of Mathematics, College of Liberal Arts & Sciences, Northern Illinois University
- Michael Sensenbrenner, Department of Computer Science, College of Liberal Arts & Sciences, Northern Illinois University
- Mahesh Raju, Graduate Student, Department of Industrial and Systems Engineering, Northern Illinois University
This project is sponsored by NIU Student Engagement Fund and Illinois Innovation Network.
We thank Dr. Allison Gladfelter, Dr. Milijana Buac, and Dr. Sinan Onal for their guidance and comments.
We thank Mahesh Raju, Dr. Sergey Uzunyan, Tracy Mereness, and Andrew Johnson for their help.