Neonatal Intensive Care Unit (NICU) nurses have plenty on their plate on a daily basis. A Mizzou Engineering researcher is part of a team working on a new device that could help lessen their load.
Roger Fales, associate professor of Mechanical and Aerospace Engineering, is partnering with Ramak Amjad and John Pardalos of MU’s Department of Child Health on an intelligent oxygen control system for NICU patients. The project is funded in part by a grant from MU’s Coulter Translational Partnership.
The ratio of oxygen to regular air that a baby in the NICU needs to receive needs to in a specific range, and presently, nurses must adjust the valve accordingly to account for fluctuations.
“The speed of response changes from baby to baby and sometimes moment to moment, so you need to adjust how quickly and the dynamics of how you respond to that,” Fales explained. “It’s usually on the order of a few minutes to re-tune. The issue is that each baby can be quite different 10 minutes later. It’s not a matter of changing just to each baby, but the changing conditions as well.”
The system developed by Fales uses an algorithm to automatically identify key parameters and adjust the amount of oxygen delivered to the baby accordingly. Should it continue down its current path and become a commercial product, it would mean one less manual process NICU nurses have to account for.
“The microcontroller reads the pulse oximetry algorithm, and using the model, it dynamically adjusts the inspired oxygen levels using this modified valve that we made,” Fales said. “It takes room air and the oxygen supply and mixes them in the right proportion, and that’s what gets sent to the baby.”
The model Fales and his team developed to tackle this problem was based off data gathered from babies on manually controlled oxygen. He said it is the first such dynamic response model to have clinical validation.
Others have tried to tackle this problem in the past, and those attempts led to Amjad reaching out to Fales to see if they could find a method that worked.
“Our algorithm is different than some things people have tried in the past,” Fales explained. “Ours is adaptive to the baby, so each baby responds differently.”
Currently, the device is in the early clinical trial stage. The next step is to do broader clinical trials and move closer to a final product for commercialization. Given the early response, Fales believes the team is on the right track.
“I think we’re on the forefront of this kind of technology, because other researchers have cited our model and our methods for modeling this dynamic system as important developments in this area,” he said.