5000 Baby Project: Screening Newborns to Develop an Algorithm for Early Detection of Neurodevelopmental Disorders

Abstract

The 5000 Baby Project aims to revolutionize the detection of developmental delays in the first months of life, enabling early diagnosis and intervention. This research utilizes clinical, evidence-based monitoring to analyze infants’ natural motor activity before six months of corrected age. The video-based sensor technology enables skeletal tracking and the development of an artificial intelligence algorithm to identify abnormal movements. This may allow researchers and clinicians to diagnose neuromuscular disorders such as autism and cerebral palsy much earlier in a child’s life. Infants are recruited from Nationwide Children’s Hospital network of clinics and the Mount Carmel St. Ann’s birthing unit. To date, our team has enrolled over 3,400 infants and recorded up to six-minute videos of each infant’s spontaneous movements while lying on their back. Our data extraction and analysis team is optimizing tracking and processing algorithms to classify infant movement as typically developing or aberrant, based on long-term developmental outcomes at ages 2 and 3. The analysis suggests the algorithm can differentiate typical from atypical movement patterns. With increasing enrollment, we aim to distinguish more specific cohorts over time to improve early identification, initiation of treatment, and gain insights into underlying causes of these disorders. This method presents a promising approach for earlier diagnosis and intervention in infants with developmental delays, potentially improving their developmental outcomes and quality of life.

How to Cite:

Rights: The Journal of Undergraduate Research at Ohio State