SBIR/STTR Research Award

SBIR Phase II: Development of a Safety System for Individuals with Alzheimer's Disease and Related Dementias

Award identifier 83775a6147d142af0f460a0ae421025c03a610f2e2e4271e382e7467803d0e91Awarding agency National Science Foundation

Award amount

$750,000

Program and phase

SBIR · Phase II

Award year

2018

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
SAFELYYOU INC.
Proposal award date
2018-04-01
Contract end date
2020-03-31
UEI
UMVJF4TJC2S6
Solicitation number
Not reported
Topic code
SH

Research abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is a video-based safety system for improving the quality and reducing the cost of dementia care. Alzheimer's Disease (AD) affects 5.4M in the US, including 1 in 9 over 65 and 1 in 3 over 85, and represents two thirds of all those affected by dementia. It is the single most expensive disease in the US ($236B direct; $221B indirect costs). The size of the US population with AD doubles every 15 years. The drug failure rate for AD is among the highest, currently 99.6. Fall accidents account for 26% of all AD related hospitalizations and are a major concern and key cost contributor, with an average fall rate of 4 falls per year and 3 in 4 repeated falls. Unfortunately, safety products developed for falls were developed for cognitively aware adults and not designed specifically for individuals with AD. The proposed system will change the quality of care and operations in memory care facilities, increase quality of life for patients and families, and help the medical profession gain a better understanding of dementia. The proposed project addresses this critical gap in Alzheimer's care by detecting safety critical events, based on camera video where events can be reviewed by a human assistant in real-time and after the fact. It is expected to achieve two main objectives that advance science and technology: (1) Demonstrating the ability for our machine learning algorithms to automatically perform safety critical tasks, by learning over a sufficiently rich set of data. These extend existing methods for fall detection to include (a) fall prediction; (b) wandering detection; (c) bed sores detections; (2) enabling the Company to demonstrate that the system proposed can run with a fully operational HIL paradigm running at scale with up to 1000 patients in 100 memory care facilities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

6 SBIR/STTR records share this UEI (2017–2019). Reported award amounts total $3,670,514. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: Department of Health and Human Services, National Science Foundation

Agency intelligence

National Science Foundation

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