Development and Validation of Baby Go App with AI for Remote Infant Motor Screening Using Home Videos to Assess Motor Skills in Term and Preterm Infants

What this Trial Is About

Researchers are evaluating the use of an artificial intelligence (AI) algorithm combined with a mobile application called "Baby Go" version 3.0 to assess infant motor development remotely at home. The study focuses on preterm and term infants aged 2 to 18 months, aiming to improve early identification and intervention for motor disorders. The goals include developing and validating the AI algorithm using home videos, comparing AI results with parental reports, examining the algorithm's ability to predict future motor outcomes, and studying the app's usability among parents and clinicians. The app "Baby Go" version 3.0 includes features for age-based motor assessment, follow-up, and educational support for parents. Parents will record videos of their infants' movements in different positions such as prone, supine, sitting, and standing every two weeks from 2 to 18 months of age and upload them via the app. Trained physiotherapists will annotate the videos to serve as a gold standard for validating the AI assessments and parental perceptions. The video data will be split for training and testing the AI model, and parents will also record when their infant first walks. Participants will be monitored through video recordings, parent and clinician surveys about app usability, and motor development measures including the Alberta Infant Motor Scale and age of walking attainment. The study will collect user experiences from parents at 6, 12, and 18 months and from clinicians at 18 months. This comprehensive approach will help assess the AI model's accuracy, predictive value, and practical use in supporting infant motor development monitoring over time.

Combined Artificial Intelligence and Mobile Application for Remote Infant Motor Screening: Development and Validation