Creating new digital tools to predict Alzheimer's and Parkinson's diseases using sleep data
Development of novel polysomnography-based digital biomarkers to predict Alzheimer’s disease and Parkinson’s disease in real world settings
This study is looking at how sleep patterns can help spot early signs of Alzheimer's and Parkinson's disease, using smart technology to make it easy for people to check their sleep at home or in a doctor's office.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Francisco NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project ID | NIH-10807908 on NIH RePORTER |
What this research studies
This research aims to develop innovative digital biomarkers based on polysomnography (PSG) sleep signals to predict Alzheimer's disease and Parkinson's disease. By utilizing advanced artificial intelligence techniques, the study will analyze various sleep-related data, including brain, heart, and muscle activity, to identify early signs of these neurodegenerative conditions. The goal is to create user-friendly and cost-effective tools that can be used both in clinical settings and at home, making early detection more accessible for patients. This approach addresses a critical need for early diagnosis, which is essential for managing these diseases effectively.
Who could benefit from this research
Good fit: Ideal candidates for this research include older adults who may be at risk for Alzheimer's or Parkinson's diseases, particularly those experiencing sleep disturbances.
Not a fit: Patients who are not elderly or do not exhibit any symptoms or risk factors for Alzheimer's or Parkinson's diseases may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate diagnoses of Alzheimer's and Parkinson's diseases, allowing for timely interventions.
How similar studies have performed: Other research has shown promise in using sleep data for predicting neurodegenerative diseases, but this approach is innovative and aims to refine and expand upon those findings.
Where this research is happening
San Francisco, United States
- University of California, San Francisco — San Francisco, United States (Active)
Researchers
- Principal investigator: Leng, Yue — University of California, San Francisco
- Study coordinator: Leng, Yue
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 below.