title: Neonatal Diagnostics: Toward Dynamic Growth Charts of Neuromotor Control.
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.
authors.affiliation: Rutgers University , Brunswick, NJ , USA.
authors.forename: Elizabeth B
authors.initials: EB
authors.lastname: Torres
authors.affiliation: University of Southern California , Los Angeles, CA , USA.
authors.forename: Beth
authors.initials: B
authors.lastname: Smith
authors.affiliation: Rutgers University , Brunswick, NJ , USA.
authors.forename: Sejal
authors.initials: S
authors.lastname: Mistry
authors.affiliation: University of Massachusetts Boston , Boston, MA , USA.
authors.forename: Maria
authors.initials: M
authors.lastname: Brincker
authors.affiliation: Rutgers University , Brunswick, NJ , USA.
authors.forename: Caroline
authors.initials: C
authors.lastname: Whyatt
keywords: accelerometers; babies; inertial measurement units; micro-movements; neural control of movement; neural development; stochastic analysis; wearable sensors