Project Details

Early Career

Status: Funded - Open

A simple method to detect neurologic disease in neonates

Dillon Chen, MD, PhD

Summary

BACKGROUND: Brain injury in newborns is difficult to detect because movement and behavior can seem normal even in neonates with large strokes or tumors. Since medical treatments and therapies early in life lead to improved outcomes, methods to detect neurologic disease as early as possible are needed improve outcomes.

GAP: Medical providers evaluate neonates over the span of a few minutes during clinical assessments, but changes in movement and behavior due to brain injury are thought to manifest subtly through slight changes only evident over long periods of time. We propose unbiased assessment using objective electronic sensors to detect those subtle changes.

HYPOTHESIS: We hypothesize that children with neurological disease will demonstrate patterns of limb movement that are different from children without neurological disease. We hypothesize that we can detect these differences using electronic movement sensors.

METHODS: We propose to attach very lightweight, low-cost motion detectors (accelerometers) to the limbs and head of neonates to obtain objective measures of movement. We will then compare movement patterns in healthy and neurologically injured neonates to define differences in the way healthy neonates and neurologically injured neonates move.

RESULTS: Pending

IMPACT: Ability to detect subtle, yet quantitatively different, movements in neonates with neurological injury will allow for early detection and intervention. This will improve motor outcomes, reducing life-long disability, decreasing suffering for neonates and their caregivers, and saving the health care system money which can be allocated to other treatment priorities.