Abstract Approximately one out of ten children born in the United States are admitted to the neonatal intensive care unit (NICU). Sleep is essential to healthy development, and researchers are investigating how to improve sleep. One major barrier to good sleep in the NICU is the frequent interruptions the infants receive. Adjusting these interruptions based on whether the infant is asleep and what state of sleep could improve sleep and thus improve healthy development. However, it is generally not possible to tell if an infant in the NICU is awake or asleep, as the behavioral repertoire is very limited as these young ages and may be further influenced by other health conditions. Furthermore, few centers have the equipment and clinical expertise to assess and analyze sleep in neonates. Thus, there is a critical need to develop technology which could provide real-time assessment of whether neonates are awake or asleep, as well as the stage of sleep. The overall goal of this proposal is to address that need by creating a real-time monitor of sleep-wake stage for neonates in the NICU. The project will additionally gather preliminary data about the device’s utility. These data include comparing feeding efficacy between cases where the infant is awoken to feed versus already being awake, influence of interruptions to sleep, and sleep changes related to medications received. This project benefits from two principal investigators, one an expert in neonatal clinical practice and research and the other a data scientist with experience developing algorithms for long term clinical neuromonitoring. Specific Aims in the R61 phase of the award include 1) developing a working prototype and conducting initial testing and verification and 2) acquiring initial use-case and pre-market data. The R33 phase of the award allows for prospective validation and verification. The immediate, expected outcome is the verified, validated device and preliminary use-case data, allowing this proposal to be directly followed by clinical research regarding how changes in practice based on real-time knowledge of sleep can improve care in the NICU. The expected, long term outcome will be a commercial device allowing translation of that research into clinical practice.