SBIR/STTR Research Award

AI-Enabled Ultra-Miniature Earpiece for Sleep Microarousal Detection and Cognitive Performance Prediction

Award identifier a16759e32895e117effdd98b54a60da947c9c5a685e86bee3587295f22f3d317Awarding agency Department of Defense · Defense Health Agency

Award amount

$1,299,698

Program and phase

SBIR · Phase II

Award year

2025

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Defense Health Agency
Recipient company
Lumia Health, Inc.
Proposal award date
2025-02-11
Contract end date
2027-06-11
UEI
H66NVU84W5L5
Solicitation number
23.3
Topic code
DHA233-002

Research abstract

This project proposes to enhance the STAT Lumia device by developing and validating the algorithm developed on phase I for detecting sleep microarousals, a key factor in assessing sleep quality and predicting cognitive performance. The Lumia, an innovative in-ear wearable, provides continuous physiological monitoring, offering significant potential for real-time sleep analysis and cognitive readiness assessment.The study will be conducted in two phases. Phase I involves recruiting 30 participants for an overnight polysomnography (PSG) sleep study, during which both standard clinical PSG data, and Lumia data will be collected. The primary focus will be on training and validating the microarousal detection algorithm, with an emphasis on accuracy across diverse sleep conditions.In Phase II, the project will evaluate the ability of the STAT device to predict next-day cognitive performance based on detected microarousals. After the overnight recordings, participants will complete a cognitive test in the lab to assess cognitive readiness. The study will analyze whether various sleep metrics derived from Lumia—such as the number of arousals, Arousal Index, total sleep time, sleep efficiency, heart rate spikes, and HRV crashes—can effectively predict next-day cognitive performance.Further, the project will refine the hardware based on feedback from human subject testing, ensuring optimal signal quality, usability, and wearability. The final phase will involve comprehensive testing to validate the device’s readiness for deployment in military and clinical settings.The project will conclude with the delivery of four fully optimized Lumia Developer Kits to the Defense Health Agency (DHA), accompanied by a detailed final report. This report will summarize Phase II outcomes, including performance metrics, algorithm accuracy, and recommendations for future research or deployment. The successful completion of this work will position the STAT Lumia device as a vital tool for real-time physiological monitoring and cognitive performance prediction, with broad applications in military operations and healthcare.

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.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

7 SBIR/STTR records share this UEI (2023–2025). Reported award amounts total $4,857,691. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.