# Utilizing Technology and AI Approaches to Facilitate Independence and Resilience in Older Adults

> **NIH NIH P30** · JOHNS HOPKINS UNIVERSITY · 2022 · $333,354

## Abstract

The U.S. population of adults aged ≥65 years will grow from 54.1 to 94.7 million by the year 
2060 and this demographic shift will be accompanied by a substantial increase in dementia 
prevalence. A growing literature supports a critical link between sleep disturbance and cognitive 
impairment and decline. Poor sleep, specifically decrements in the slow-wave oscillations that 
occur during non-rapid eye movement (NREM) slow-wave sleep (SWS), are being studied as 
possible points of intervention. During SWS, memory traces encoded during the day are 
reactivated, strengthened, and transferred from the hippocampus to the neocortex, where they 
become more durable, long-term memories. Thus, SWS shows promise as a target for 
therapies aimed at modulating AD pathophysiology and slowing or even preventing AD. Within 
this proposal, we are developing a wearable technology that slows cognitive decline in older 
adults in the comfort of their own homes. Our digital therapeutic employs an EEG headband and 
closed-loop neurostimulation to enhance brain activity during slow wave sleep. By adapting this 
technology to the unique needs of older adults and packaging the complex sensors, circuitry, 
and algorithms into a comfortable headband, we are translating this laboratory technique into an 
accessible therapy.

## Key facts

- **NIH application ID:** 10652093
- **Project number:** 3P30AG073104-02S2
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Peter M. Abadir
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $333,354
- **Award type:** 3
- **Project period:** 2021-09-30 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10652093

## Citation

> US National Institutes of Health, RePORTER application 10652093, Utilizing Technology and AI Approaches to Facilitate Independence and Resilience in Older Adults (3P30AG073104-02S2). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10652093. Licensed CC0.

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