AI-Powered Wearable Suit Tracks Infant Motor Development with Accuracy: Study
Researchers have created a sensor-equipped wearable jumpsuit that uses AI to track infants' gross motor milestones with over 90% accuracy. As reported in Paediatrics, the suit's measurements closely matched parental reports and international benchmarks.
Early development of gross motor skills is foundational for the upcoming neurocognitive performance. Here, we studied whether at-home wearable measurements performed by the parents could be used to quantify and track infants’ developing motor abilities.
Unsupervised at-home measurements of the infants’ spontaneous activity were made repeatedly by the parents using a multisensor wearable suit (altogether 620 measurements from 134 infants at age 4–22 months).
Machine learning-based algorithms were developed to detect the reaching of gross motor milestones (GMM), to measure times spent in key postures, and to track the overall motor development longitudinally. Parental questionnaires regarding GMMs were used for developing the algorithms, and the results were benchmarked with the interrater agreement levels established by the World Health Organization (WHO). A total of 97 infants were used for the algorithm development and cross-validation, whereas an external validation was done using 37 infants from an independent recruitment in the same hospital. RESULTS: The algorithms detected the reaching of GMMs very accurately (cross-validation: accuracy, 90.9%-95.5%; external validation, 92.4%-96.8%), which compares well with the human experts in the WHO reference study.
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