Improving CPR effectiveness during cardiac arrest with advanced technology
Official title: A deep learning artifact removal method for CPR continuity throughout the shock decision in AEDs
Funded at University of Connecticut Storrs · NIH-11062247 · Data updated 2026-11-12
This study is working on a way to make CPR more effective during heart emergencies by improving how heart rhythm is read while chest compressions are happening, which could help save more lives when someone has a cardiac arrest.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Connecticut Storrs NIH-funded |
| Lab location | 1 site (Storrs-Mansfield, United States) |
| Project start | June 1, 2025 |
| Project end | March 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $752,495 |
| NIH project number | 1R01HL173935-01A1 |
| Project ID | NIH-11062247 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals aged 21 and older who experience out-of-hospital cardiac arrest.
✕Less likely to help
Patients who are not experiencing cardiac arrest or those under 21 years old may not benefit from this research.
What this research studies
This research focuses on enhancing the effectiveness of cardiopulmonary resuscitation (CPR) during out-of-hospital cardiac arrest by developing a method to remove motion artifacts from electrocardiogram (ECG) signals caused by chest compressions. The project aims to create a comprehensive database of CPR artifact data and utilize deep learning techniques to improve the accuracy of shock decisions made by automated external defibrillators (AEDs). By ensuring continuous high-quality CPR without interruptions for rhythm analysis, the research seeks to improve survival rates for patients experiencing cardiac arrest.
Why it matters
Potential benefit: If successful, this research could significantly increase survival rates for patients experiencing out-of-hospital cardiac arrest by enabling more effective and uninterrupted CPR.
How similar studies have gone: Previous research has shown promise in using advanced algorithms to improve CPR outcomes, but this specific approach to artifact removal in AEDs is relatively novel.
Where this research is happening
-
University of Connecticut Storrs
Storrs-Mansfield, United States Active
Researchers
- Principal investigator: Chon, Ki H — University of Connecticut Storrs
- Study coordinator: Chon, Ki H
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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.