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Digital Twins for Monitoring Neuromotor Development in Preterm Infants: Conceptual Framework and Proof-of-concept

Sara Montagna1, Rita Stagni2, Giada Pierucci3

  • 1Department of Pure and Applied Sciences, University of Urbino, Urbino, Italy. sara.montagna@uniurb.it.

Journal of Medical Systems
|October 23, 2025
PubMed
Summary

Digital Twins (DTs) offer a novel approach to monitor infant motor development, crucial for predicting neurodevelopmental disorders (NDDs). This technology integrates multimodal data for holistic, longitudinal evaluations, improving early identification of developmental deviations.

Keywords:
Digital Twin technologyMotor developmentNeurodevelopmental disordersPreterm birthWearable sensors

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Area of Science:

  • Pediatric Neurodevelopment
  • Computational Medicine
  • Infant Motor Assessment

Background:

  • Preterm birth significantly increases risks for motor, cognitive, and behavioral impairments in children.
  • Early motor development monitoring is vital for predicting neurodevelopmental disorders (NDDs).
  • Current assessment methods lack quantitative, standardized measures and struggle with integrating complex medical histories.

Purpose of the Study:

  • To introduce a novel framework using Digital Twins (DTs) and advanced metrics for holistic, longitudinal infant motor development assessment.
  • To overcome limitations in current infant motor assessment by integrating multimodal data and sophisticated analysis.
  • To support early identification and prediction of neurodevelopmental disorders in infants.

Main Methods:

  • Development of a Digital Twin (DT) ecosystem integrating data processing algorithms and AI for analysis.
  • Implementation of a proof-of-concept application using published data from full-term, preterm, and very preterm infants.
  • Standardization of motor, clinical, and cognitive data within the DT model for advanced analyses.

Main Results:

  • Demonstrated the feasibility of the DT framework in integrating diverse infant data (motor, clinical, cognitive).
  • Showcased initial advanced analyses integrating standardized measures within the DT.
  • Validated the potential for a scalable and adaptable solution for infant monitoring.

Conclusions:

  • The proposed DT approach offers a significant advancement for clinical practice in monitoring preterm infant motor trajectories.
  • This scalable framework can be adapted for large, multi-center studies across various infant populations requiring motor function monitoring.
  • DTs provide a powerful tool for holistic, longitudinal evaluations, enhancing the prediction and management of NDDs.