# Augmented Preclinical Alzheimer's Disease Detection Through Wearable Health and Driving Behavior Data.

> **NIH NIH R43** · AMISSA, INC. · 2024 · $505,516

## Abstract

PROJECT SUMMARY
 By 2050, 88 million (20%) Americans will be ≥ age 65, representing a doubling of the population along
with 25% of all drivers being an older adult. Given that there exists a long preclinical stage of Alzheimer's disease
(AD) lasting around 20 years, there is a need to develop low-cost modifiable behavioral interventions. The
proposed study expands on the substantial work by two teams: 1) Amissa Health’s NIH SBIR-funded research
platform that allows for remote patient monitoring through commodity smartwatches (e.g., an Apple Watch) and
2) The NIH/NIA-funded DRIVES Project from Washington University School of Medicine in St. Louis that uses
in-vehicle driving loggers to capture driving behaviors in individuals with and without preclinical AD. This study
aims to investigate the relationship between health-related data collected from the Amissa Platform and Apple
Watch among older adults coupled with driving behavior data to classify preclinical AD status.
 Aim 1 focuses on assessing the relationship between health-related data collected from the Amissa
Platform and Apple Watch and cognitive function in older adults with and without preclinical AD. A cohort of
cognitively normal older adults (≥ age 65, n=50) will be recruited from an existing DRIVES Project. The participant
preclinical AD status will have been determined using amyloid tracers via Positron Emission Tomography (PET).
In addition, neuropsychological assessments will be administered to participants to comprehensively evaluate
cognitive functions such as memory, attention, executive functions, and visuospatial abilities. Health-related
parameters, such as heart rate, oxygen saturation, sleep patterns, and physical activity, will be continuously
recorded using the Apple Watch and AmissaWear. The data will be analyzed to identify relationships in health-
related parameters and cognition by preclinical AD status.
 The goal of Aim 2 is to determine whether health-related data from the Amissa Platform and Apple Watch,
combined with real-world driving behavior data, collected from in-vehicle loggers, can predict preclinical AD
status. Participants from Aim 1 will be equipped with DRIVES chips to continuously capture driving performance
metrics, including speed, acceleration, braking, and lane deviations. The second Aim will integrate the collected
wearable health sensor data with driving data with the goal of developing a robust machine learning model to
predict preclinical AD status. This model aims to augment the existing neuropsychological assessment
techniques with lower-biased health sensor and driving behavior data and to better estimate cognitive decline
and driving risks among older drivers.
 This innovative research project introduces novel approaches, including the use of popular smartwatches
for data collection, a centralized biometric database for AD research, and the integration of health and driving
data. It aims to provide accessible and stigma-free data collecti...

## Key facts

- **NIH application ID:** 11008460
- **Project number:** 1R43AG087803-01A1
- **Recipient organization:** AMISSA, INC.
- **Principal Investigator:** Jon Andrew Corkey
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $505,516
- **Award type:** 1
- **Project period:** 2024-09-01 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11008460

## Citation

> US National Institutes of Health, RePORTER application 11008460, Augmented Preclinical Alzheimer's Disease Detection Through Wearable Health and Driving Behavior Data. (1R43AG087803-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11008460. Licensed CC0.

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