Deep learning to predict obstruction site and guide sleep apnea treatment
Official title: Deep Learning of Snoring to Predict Collapse Site, Treatment Outcomes, and its Clinical Translation in Obstructive Sleep Apnea
Funded at Kennesaw State University · NIH-11445428 · Data updated 2026-11-12
A patient-focused project uses snoring sounds and AI to predict where your airway collapses during sleep and to guide personalized treatments.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Kennesaw State University NIH-funded |
| Lab location | 1 site (Kennesaw, United States) |
| Project start | September 1, 2026 |
| Project end | August 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $235,520 |
| NIH project number | 1R21HL188520-01 |
| Project ID | NIH-11445428 on NIH RePORTER |
Who could benefit from this research
✓Could help
Adults with obstructive sleep apnea who are candidates for CPAP, MAD, HGNS, or other airway-targeted therapies.
✕Less likely to help
People whose sleep apnea is not related to airway collapse patterns or who are not eligible for the targeted therapies might see limited benefit.
What this research studies
This project aims to use deep learning analysis of snoring sounds to identify the likely site of airway collapse in obstructive sleep apnea. By linking acoustic patterns to collapse sites, it seeks to tailor treatment choices such as CPAP, MAD, or nerve stimulation to the individual. The work emphasizes making non-invasive tools available to help decide the best therapy without invasive testing when possible. It includes plans to translate findings into clinical practice to improve comfort and adherence for people with OSA.
Why it matters
Potential benefit: If successful, this approach could help choose the most effective, tolerable treatment for sleep apnea based on a person’s snoring, potentially improving adherence and outcomes.
How similar studies have gone: Prior studies suggest acoustic features can reflect airway collapse patterns, but translating this into a widely accessible clinical biomarker is still being explored.
Where this research is happening
-
Kennesaw State University
Kennesaw, United States Active
Researchers
- Principal investigator: Saha, Shumit — Kennesaw State University
- Study coordinator: Saha, Shumit
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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.