NEONAID - Neonatal Online Neuro-Analysis for Interpretation and Decision-support - Bringing automated neonatal monitoring to the bedside

From 01-09-2024 to 31-08-2026

Description

Even though huge progress has been made in order to reduce the mortality of prematurely born infants, the risk for adverse health outcome and neurodevelopmental disability has increased. This, together with an increasing rate of premature births, represents a huge burden in our society. In order to reduce this burden and improve neonatal care, appropriate tools to early identify the neonates with higher risk of adverse outcomes should be developed. In the past, we have developed a variety of advanced algorithms that quantify EEG patterns and autoregulation which can support the identification of such neonates. These algorithms provide an automated, objective and interpretable analysis of the complex biomedical signals, but so far have only been validated offline on carefully selected recordings. The current project aims at making those algorithms more robust to variations in signal quality observed on the ward, as well as providing reliability scores for their output so that they can be routinely used at the bedside. Additionally, we aim to bring these algorithms to the bedside in the NICU with MDR approval in order to demonstrate the clinical impact. In parallel, the project will evaluate valorisation strategies such as tele-monitoring for neonatal care units.

Team

• Maarten De Vos, Coordinator

Financing

Funding: KU Leuven - Internal Funding KU Leuven

Program/Grant Type: C3 - KU Leuven Category 3 Funding