Predicting and continuously monitoring breathlessness with noninvasive signals
Official title: Predicting and continuously monitoring dyspnea using noninvasive biomarkers
Funded at University of California Riverside · NIH-11366620 · Data updated 2026-11-12
A study to create a machine-learning tool that uses easy-to-measure body signals to predict when patients feel breathless, even if they can’t communicate.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California Riverside NIH-funded |
| Lab location | 1 site (Riverside, United States) |
| Project start | September 9, 2026 |
| Project end | May 31, 2031 |
| Funding year | 2026 |
| Award (this year) | $709,201 |
| NIH project number | 1R01HL179283-01A1 |
| Project ID | NIH-11366620 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with chronic or critical illnesses who experience dyspnea and can provide physiological data via noninvasive monitoring.
✕Less likely to help
Patients without breathlessness or those unable to provide necessary physiological signals may not benefit.
What this research studies
This project aims to develop and validate a noninvasive, continuously monitoring system that uses common physiological signals to predict dyspnea. Researchers will gather data from patients with chronic or critical illnesses and build algorithms that translate signals like oxygen saturation, CO2 levels, heart activity, and breathing drive into a dyspnea score. The goal is to provide clinicians with a reliable, real-time tool to detect and monitor breathlessness, improving timely care and comfort for patients. The work builds on promising preliminary results showing high accuracy in detecting induced dyspnea and plans two integrated aims to refine and validate the predictive model.
Why it matters
Potential benefit: If successful, patients could experience quicker recognition and relief of breathlessness, leading to better comfort and fewer complications.
How similar studies have gone: Previous data suggest that noninvasive signals can predict dyspnea with good accuracy, supporting further development in a larger, real-world setting.
Where this research is happening
-
University of California Riverside
Riverside, United States Active
Researchers
- Principal investigator: Heinrich, Erica — University of California Riverside
- Study coordinator: Heinrich, Erica
Related research
Other NIH-funded projects on the same topics.
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Patient-centered risk profiling to tailor breathlessness care
A study from UCLA aims to use AI to identify why a smoker experiences shortness of breath and tailor care to each person.
-
Understanding how the brain shapes breathing to help people with persistent breathlessness
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-
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-
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Researchers are recording brain signals from people who already have implanted epilepsy electrodes to understand how higher brain regions produce ongoing breathlessness in conditions like COPD, asthma, heart or neuromuscular disease.
-
Brief behavioral support to help breathlessness in advanced lung cancer
A multi-site study tests a short behavioral program delivered by nurses to help adults with advanced lung cancer feel less breathless and more able to do daily activities.
-
Personalized oxygen therapies for cancer-related breathing difficulties
This study is looking to help people with advanced cancer who are having trouble breathing by comparing a special program led by respiratory therapists to regular care, to see which one works better at making breathing easier.
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.