# A Comprehensive Fall Prevention System for Memory Care: Final Feasibility and Randomized Controlled Study

> **NIH NIH R44** · SAFELYYOU, INC. · 2020 · $536,666

## Abstract

Abstract
In the US, Alzheimer’s disease (AD) is the single most expensive disease, the only disease in the top six
for which the number of deaths is increasing. The greatest cost contributors are frequent
hospitalizations, where falls are the largest culprit, and frequent need for assistance with the activities
of daily living. Fall safety systems show the potential to reduce costs and increase quality of care by
reducing the likelihood of emergency events (e.g., detecting falls before a fracture occurs and reducing
the number of repeat falls). Unfortunately, current safety devices require wearable or sensor technology
not suitable for individuals with dementia and incapable of showing caregivers how falls occur.
Our goal is to extend the impacts of SafelyYou Guardian, an online fall detection system with off-the-
shelf wall-mounted cameras to automatically detect falls for patients with AD and related dementias
(ADRD), enabled by a human-in-the-loop (HIL). The HIL, who can monitor several facilities at a time,
confirms the fall detection alerts provided by our artificial intelligence algorithms, and places a call to
the facilities, so an intervention can happen within minutes of the fall detection (as opposed to hours
after, when the next scheduled visit to the room of the patient happens). Subsequently, an Occupational
Therapist (OT) reviews the fall videos to make recommendations on how to re-organize the patient
space (intervention), to prevent future falls. We leverage our HIL paradigm, in which our deep learning
(a subfield of artificial intelligence) approaches identify and pre-filter falls well enough to leave the last
check to a human, who will call the facilities in case of detected safety critical events (falls).
The present Fast Track NIH SBIR project leverages the already recruited 100 patients in our partner 11
memory care facilities, recruited through our previous IRB-approved pilots, which we leverage:
 · Pilot 1: We demonstrated the feasibility of the system by collecting proof-of-concept data
 containing 200 acted falls of healthy subjects and showed accurate fall detection.
· Pilot 2: We demonstrated acceptance of privacy/safety tradeoffs by patients, family and staff,
 through the collection of 3 months of video data at WindChime of Marin, a memory care facility
 from the Integral Senior Living network, in which we identified 4 total hours of fall data. This led
 to clinical benefits including an 80% fall reduction through the intervention of an Occupational
 Therapist (OT) to re-organize patient space.
· Pilot 3: We demonstrated scalability and acceptance by deploying the system in 11 facilities,
 totaling 100 patients monitored by our system (offline, no HIL intervention).
· Pilot 4 (ongoing): We demonstrated the ability to perform online (real-time) fall detection, with
 real-time intervention of the HIL through our partner company Magellan-Solutions, which
 provides the 24/7 monitoring service for the facilities, and confi...

## Key facts

- **NIH application ID:** 10018603
- **Project number:** 5R44AG062088-03
- **Recipient organization:** SAFELYYOU, INC.
- **Principal Investigator:** George Netscher
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $536,666
- **Award type:** 5
- **Project period:** 2018-09-30 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10018603

## Citation

> US National Institutes of Health, RePORTER application 10018603, A Comprehensive Fall Prevention System for Memory Care: Final Feasibility and Randomized Controlled Study (5R44AG062088-03). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10018603. Licensed CC0.

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