Non-Invasive AI-Enhanced Neonatal Blood Pressure Monitoring in NICUs
Official title: BPAlert: A Non-Invasive, AI-Enhanced, Continuous Blood Pressure Monitoring System for Neonates in NICU
Funded at Rutgers, the State Univ of N.j. · NIH-11442500 · Data updated 2026-11-12
A new AI-powered system uses the baby’s existing sensors to continuously track blood pressure in the NICU without invasive procedures, helping clinicians spot problems early.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Rutgers, the State Univ of N.j. NIH-funded |
| Lab location | 1 site (Piscataway, United States) |
| Project start | September 1, 2026 |
| Project end | August 31, 2029 |
| Funding year | 2026 |
| Award (this year) | $235,500 |
| NIH project number | 1R21EB040115-01 |
| Project ID | NIH-11442500 on NIH RePORTER |
Who could benefit from this research
✓Could help
Newborns in NICUs who require BP monitoring and can be safely observed with non-invasive sensors.
✕Less likely to help
Newborns for whom non-invasive monitoring is not feasible or in whom PPG-based signals cannot be obtained.
What this research studies
This project aims to provide continuous, non-invasive blood pressure monitoring for newborns in the NICU by combining AI-driven estimations of BP changes with periodic cuff measurements. The system relies on photoplethysmography, a light-based signal already used for oxygen monitoring, and a self-explaining AI design to show clinicians why a prediction is made. By focusing on BP changes over short intervals rather than absolute values, it seeks to improve accuracy and generalizability across patients while maintaining transparency. An integrated alarm component will alert care teams when BP changes signal potential sepsis or organ issues, supporting timely clinical decisions.
Why it matters
Potential benefit: If successful, this system could enable continuous BP monitoring with fewer invasive procedures, potentially improving early detection of critical conditions in newborns.
How similar studies have gone: Prior AI-based BP-estimation efforts exist, but this approach emphasizes ∆BP estimation and self-explaining AI to improve reliability and clinician trust.
Where this research is happening
-
Rutgers, the State Univ of N.j.
Piscataway, United States Active
Researchers
- Principal investigator: Najafizadeh, Laleh — Rutgers, the State Univ of N.j.
- Study coordinator: Najafizadeh, Laleh
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.