Using everyday digital data to find early signs of dementia and reduce disparities
A Next Generation Data Infrastructure to Understand Disparities across the Life Course
This project will build large real-world digital health datasets and AI tools to help spot early memory and thinking changes and the everyday factors that raise dementia risk, especially in groups hit hardest.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Southern California NIH-funded |
| Lab location | 1 site (Los Angeles, UNITED STATES) |
| Project ID | NIH-11201652 on NIH RePORTER |
What this research studies
Researchers will collect person-generated health data from smartphones, wearables, and measures of daily activities to capture real-life patterns of thinking, behavior, and function. They will combine, standardize, and share these data as benchmark datasets to train transparent, interpretable AI/ML models. The work focuses on groups with higher Alzheimer’s and related dementia (ADRD) risk, such as people with diabetes, and on detecting subtle changes that can appear years before clinical diagnosis. The goal is to identify modifiable risk factors and support targeted behavioral approaches that could reduce long-term ADRD burden.
Who could benefit from this research
Good fit: Ideal participants are older adults, including people with higher risk like diabetes, who use smartphones or wearables and are willing to share everyday activity and health data.
Not a fit: People without access to digital devices, those unable to share personal digital data, or individuals with very advanced dementia are less likely to benefit directly from this project.
Why it matters
Potential benefit: If successful, this could enable earlier, more personalized detection of dementia risk and guide behavior changes that help slow or prevent decline.
How similar studies have performed: Small studies using sensors and smartphone data have shown promise for detecting cognitive change, but large, disease-focused benchmark datasets and transparent AI models like this remain novel.
Where this research is happening
Los Angeles, UNITED STATES
- University of Southern California — Los Angeles, United States (Active)
Researchers
- Principal investigator: Kapteyn, Arie — University of Southern California
- Study coordinator: Kapteyn, Arie
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.