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Updated: Mar 10, 2026
Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
Neonatal Diagnostics: Toward Dynamic Growth Charts of Neuromotor Control
Elizabeth B Torres1, Beth Smith2, Sejal Mistry1
1Rutgers University , Brunswick, NJ , USA.
Insights
New analytics on infant growth charts can identify neurodevelopmental risks early. This method tracks neuromotor control development, aiding timely intervention for developmental disorders.
Area of Science:
- Pediatric Development
- Neurodevelopmental Disorders
- Biostatistics
Background:
- Neurodevelopmental disorders (NDDs) are rising, necessitating early detection and intervention.
- Standard pediatric growth charts have limitations in predicting NDDs due to reliance on linear models.
- Current charts obscure crucial statistical information in non-linear growth patterns and skewed distributions.
Purpose of the Study:
- To develop and demonstrate a novel analytical method for early detection of neurodevelopmental risk.
- To improve upon the predictive capabilities of traditional growth charts for identifying developmental issues.
- To assess the utility of velocity-based growth charts combined with motor performance analysis.
Main Methods:
- Longitudinal growth data from 36 newborns over 5 months were analyzed.
- Incremental (velocity-based) growth charts were employed instead of standard charts.
- Dynamic growth changes were integrated with motor performance data, analyzing the signal transition from random noise.
Main Results:
- The new analytical method successfully detected early stunting in voluntary neuromotor control development.
- The approach demonstrated the ability to flag infants at risk for neurodevelopmental derailment.
- This method offers a more sensitive approach to analyzing growth data for developmental trajectories.
Conclusions:
- Velocity-based growth charting combined with motor performance analysis provides a powerful tool for early neurodevelopmental risk detection.
- This approach can significantly enhance pediatricians' ability to identify and intervene in potential developmental disorders.
- Further research can refine these analytics for broader application in developmental pediatrics.
Abstract:
The current rise of neurodevelopmental disorders poses a critical need to detect risk early in order to rapidly intervene. One of the tools pediatricians use to track development is the standard growth chart. The growth charts are somewhat limited in predicting possible neurodevelopmental issues. They rely on linear models and assumptions of normality for physical growth data - obscuring key statistical information about possible neurodevelopmental risk in growth data that actually has accelerated, non-linear rates-of-change and variability encompassing skewed distributions. Here, we use new analytics to profile growth data from 36 newborn babies that were tracked longitudinally for 5 months. By switching to incremental (velocity-based) growth charts and combining these dynamic changes with underlying fluctuations in motor performance - as the transition from spontaneous random noise to a systematic signal - we demonstrate a method to detect very early stunting in the development of voluntary neuromotor control and to flag risk of neurodevelopmental derail.
