Continuous monitor to better detect and classify apnea in premature newborns
Official title: Continuous Respiratory Monitoring Platform for Classifying Apnea of Prematurity
Funded at Makani Science, INC. · NIH-11318949 · Data updated 2026-11-12
A small multimodal breathing monitor plus smart software designed to automatically tell what kind of apnea premature babies are having.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Makani Science, INC. NIH-funded |
| Lab location | 1 site (Irvine, United States) |
| Project start | April 9, 2025 |
| Project end | February 28, 2027 |
| Funding year | 2026 |
| Award (this year) | $362,934 |
| NIH project number | 5R61HL177500-02 |
| Project ID | NIH-11318949 on NIH RePORTER |
Who could benefit from this research
✓Could help
Premature infants in the neonatal intensive care unit (especially those 0–4 weeks old) who are at risk for or have episodes of apnea and are receiving care at participating centers.
✕Less likely to help
Full-term infants without apnea, older infants, or babies cared for outside participating hospitals would likely not benefit from this specific project.
What this research studies
This project will build a tiny multimodal monitor made for premature infants and pair it with machine learning to classify apneas as central, obstructive, or mixed. During the first phase the team will design and test the hardware and software prototypes and collect initial breathing and physiological data at a collaborating children’s hospital. Sensors will record breathing, heart rate, and movement and feed that data into algorithms trained to recognize apnea types. The goal is continuous, more accurate monitoring that can help guide care and safety for newborns and provide better data for researchers.
Why it matters
Potential benefit: If successful, this could provide more accurate, continuous detection and automatic classification of apnea in preterm infants, helping clinicians treat newborns more precisely and safely.
How similar studies have gone: Existing commercial monitors often miss or misclassify apnea in preemies, and combining newborn-specific sensors with machine learning is a promising but relatively new approach with limited prior clinical success in apnea of prematurity.
Where this research is happening
-
Makani Science, INC.
Irvine, United States Active
Researchers
- Principal investigator: Chu, Michael — Makani Science, INC.
- Study coordinator: Chu, Michael
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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.