Abstract & Details
Description
Award ID: 2537536
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is the development of a needle-free, wearable device for continuous blood glucose monitoring. Todays glucose monitors require a sensor inserted under the skin that must be replaced every 1014 days, creating pain, inconvenience, and high costs that discourage many people from using them. This project will explore a new optical technology that measures glucose without breaking the skin, making monitoring more comfortable, affordable, and accessible. If successful, this approach could empower millions of people with diabetes and prediabetes to better understand and manage their health, reducing complications and healthcare costs. Beyond medical use, the device could also serve the growing wellness market, where consumers track nutrition and fitness through wearable technology. Public investment in this research supports national goals of advancing healthcare innovation, reducing chronic disease burdens, and driving U.S. leadership in next-generation biosensing technology. This Small Business Innovation Research (SBIR) Phase I project will investigate a high-risk, high-reward innovation: a broadband optoelectronic platform for non-invasive, continuous glucose monitoring. The primary technical challenge is achieving clinical-grade accuracy across variable users and environments, a feat that has eluded decades of prior attempts. The proposed device employs volumetric spatiotemporal spectroscopy across the visible, near-infrared, and shortwave infrared spectrum (5002500 nm), capturing depth-resolved optical signals over a broad skin surface. This rich dataset will be interpreted through physics-informed machine learning models that separate glucose-specific absorption features from confounding signals such as tissue scattering, temperature fluctuations, motion artifacts, and ambient light. The scope of Phase I includes optimizing source-detector geometry to maximize sensitivity, implementing closed-loop temperature compensation to suppress thermal drift, integrating digital lock-in amplification for noise rejection, and compensating for motion artifacts and device coordinate shifts with a real-time Inertial Measurement Unit. A pilot human subjects study will validate the systems ability to generate reproducible optical data under real-world conditions. Success will be measured by inter-subject mean absolute relative difference (MARD) compared to invasive continuous glucose monitors, signal stability across variable environmental conditions, and demonstration of scalable design for future manufacturing. 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.
NSF Program Director: Henry Ahn
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is the development of a needle-free, wearable device for continuous blood glucose monitoring. Todays glucose monitors require a sensor inserted under the skin that must be replaced every 1014 days, creating pain, inconvenience, and high costs that discourage many people from using them. This project will explore a new optical technology that measures glucose without breaking the skin, making monitoring more comfortable, affordable, and accessible. If successful, this approach could empower millions of people with diabetes and prediabetes to better understand and manage their health, reducing complications and healthcare costs. Beyond medical use, the device could also serve the growing wellness market, where consumers track nutrition and fitness through wearable technology. Public investment in this research supports national goals of advancing healthcare innovation, reducing chronic disease burdens, and driving U.S. leadership in next-generation biosensing technology. This Small Business Innovation Research (SBIR) Phase I project will investigate a high-risk, high-reward innovation: a broadband optoelectronic platform for non-invasive, continuous glucose monitoring. The primary technical challenge is achieving clinical-grade accuracy across variable users and environments, a feat that has eluded decades of prior attempts. The proposed device employs volumetric spatiotemporal spectroscopy across the visible, near-infrared, and shortwave infrared spectrum (5002500 nm), capturing depth-resolved optical signals over a broad skin surface. This rich dataset will be interpreted through physics-informed machine learning models that separate glucose-specific absorption features from confounding signals such as tissue scattering, temperature fluctuations, motion artifacts, and ambient light. The scope of Phase I includes optimizing source-detector geometry to maximize sensitivity, implementing closed-loop temperature compensation to suppress thermal drift, integrating digital lock-in amplification for noise rejection, and compensating for motion artifacts and device coordinate shifts with a real-time Inertial Measurement Unit. A pilot human subjects study will validate the systems ability to generate reproducible optical data under real-world conditions. Success will be measured by inter-subject mean absolute relative difference (MARD) compared to invasive continuous glucose monitors, signal stability across variable environmental conditions, and demonstration of scalable design for future manufacturing. 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.
NSF Program Director: Henry Ahn
| Status | Active |
|---|---|
| Effective start/end date | 07/01/26 → 06/30/27 |
Funding
- SBIR Phase I: $304,898.00
Active Fiscal Year
- FY2027
- FY2026
Start Fiscal Year
- FY2026
TIP Programs
- SBIR Phase I
Small Business
- Yes
Key Technology Areas
- Artificial Intelligence
- (confidence score: 82%)
- Biotechnology
- (confidence score: 85%)
- Advanced Computing and Semiconductors
- (confidence score: 83%)
Technology Foci
- Synthetic Biology
- (confidence score: 98%)
- Semiconductors
- (confidence score: 92%)
- Artificial Intelligence (Broad)
- (confidence score: 100%)
Congressional District at Award
- District n. 07 of Massachusetts
Current Congressional District
- District n. 08 of Massachusetts
United States
- Massachusetts
Core Based Statistical Area (CBSA)
- Boston-Cambridge-Newton, MA-NH
County
- County: Suffolk, MA
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