# Novel application of Digital signals of movement, sleep and heart rhythms for detection of Alzheimer's Disease and Related Dementias

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2024 · $771,564

## Abstract

PROJECT SUMMARY
Early detection of cognitive and functional decline is a major goal of the NIA in its fight against Alzheimer's
Disease and Related Dementias (ADRD). Physical, physiological, and cognitive changes associated with ADRD
may emerge years prior to clinical manifestations, thus there is an urgent need for novel, cost-effective,
noninvasive, and scalable tools to improve detection of ADRD risk. Older adults with cognitive impairment often
exhibit changes in movement, sleep, and heart rhythms, suggesting possible shared vascular or
neurodegenerative pathways. Emerging research from our group and others links digital signals from movement,
sleep, and heart rhythms with brain and cognitive health; however, knowledge gaps remain in the associations
among these signals and brain and cognitive health across the cognitive spectrum. In response to NOT-AG-20-
017, this application will directly address these gaps using existing and ongoing/new data collection from
wearable technology (7-day accelerometry and 14-day ambulatory electrocardiogram (ECG)), cognitive
assessments (neuropsychological battery, adjudicated cognitive diagnosis), and neuroimaging (florbetapir PET
for beta amyloid (Aβ), 3T brain MRI for neurodegeneration and white matter disease) from ≥1000 older adults
participating in the Atherosclerosis Risk in Communities (ARIC) Neurocognitive Study. We will use novel analytic
approaches to integrate movement, sleep, and heart rhythm features and assess their individual and joint
associations with brain and cognitive health. Our overarching goal is to identify clinically relevant digital
biomarkers that combine movement, sleep, and heart rhythm signals as sensitive indicators of cognitive function,
cognitive trajectories, ADRD pathology, and cognitive diagnosis. To this end, this research will inform the future
use of wearable devices in large-scale studies, provide novel targets for screening and early detection of ADRD
in disease stages during which intervention and treatment are more likely to be effective, and aid in identifying
high-risk participants for prevention trials.

## Key facts

- **NIH application ID:** 10880669
- **Project number:** 5R01AG075883-03
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Lin Yee Chen
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $771,564
- **Award type:** 5
- **Project period:** 2022-09-30 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10880669

## Citation

> US National Institutes of Health, RePORTER application 10880669, Novel application of Digital signals of movement, sleep and heart rhythms for detection of Alzheimer's Disease and Related Dementias (5R01AG075883-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10880669. Licensed CC0.

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