Artificial Intelligence for Infant Motor Screening: Development and Validation

The purpose of this three-year study is therefore three-fold: (1) Model Development- to apply pose estimation model and tracking recognition model on the movements of a large sample of term and preterm infants under a motor assessment in the laboratory to examine the accuracy of the AI algorithms in identifying individual movements using physical therapists' results as gold standards; (2) Model Validation- to examine the performance of the AI algorithms on the same term and preterm infants' movements when video recorded by the parents at home between the laboratory assessment ages using physical therapists' results as gold standards; and (3) Concurrent and Predictive Validity of AI Movement Sets- to select the identifiable movement classes into AI movement sets for individual ages to examine their concurrent validity with physical therapists' results and predictive validity on developmental outcomes at 18 months of age in these infants.