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Miniaturized Breath-based Sensor for the Detection of Hypo- and Hyperglycemia

Miniaturized Smart Sensor Device for the Detection of Hypo- and Hyperglycemic Events in Persons Diagnosed With Diabetes

Status
Recruiting
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07696273
Enrollment
40
Registered
2026-07-10
Start date
2026-05-31
Completion date
2027-10-01
Last updated
2026-07-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Diabetes, Hyperglycemia, Hypoglycemia (Diabetic)

Keywords

Exhaled Breath Analysis, Volatile Organic Compounds (VOCs), Metal Oxide Sensors, Gas Chromatography, Mass Spectrometry

Brief summary

The purpose of this study is to determine whether an array of biosensors can noninvasively identify hyperglycemic or hypoglycemic events in persons diagnosed with diabetes through noninvasive detection of volatile organic compounds (VOCs) in exhaled breath.

Detailed description

At this stage, the team will deploy two different analytical platforms in parallel in a clinical study to survey exhaled breath volatile organic compound (VOC) profiles at a diabetes youth camp. The ultimate objective is to determine whether a miniaturized laboratory device incorporating metal oxide gas sensors can reliably distinguish specific VOCs associated with glycemic events under real-world conditions. Sensor responses will be validated through parallel breath collection using Tedlar (plastic) bags, followed by confirmatory analysis via gas chromatography-mass spectrometry (GC-MS).

Interventions

DEVICESensing Device and Tedlar Bags

Children diagnosed with diabetes that wear a continuous glucose monitor (CGM) will provide breath samples into the miniaturized sensing device (as well as Tedlar bags for GC-MS analysis) during euglycemia, hypoglycemia, and hyperglycemia. The breath data will be analyzed to draw correlations with blood glucose levels measured via CGMs and finger prick tests.

Sponsors

Indiana University
Lead SponsorOTHER

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
7 Years to 25 Years
Healthy volunteers
No

Inclusion criteria

* Who are diagnosed with T1D or T2D. * Who are between 7-25 years of age. * That use a Dexcom (G6 or G7) CGM device. * That have an established working CGM for at least 12 hours. * That are willing to share their CGM data for the study duration. * That are willing and able to fill up a breath collection bag. * That are attending a diabetes camp in the state of Indiana.

Exclusion criteria

* That are smokers or who live with someone who smokes in their vicinity (including prior to attending camp). * That have a condition or abnormality other than T1D/T2D that in the opinion of the Investigators would compromise the safety of the subject or the quality of the data. * That have symptoms or recently been diagnosed with an upper respiratory illness including COVID-19 (or other viral/bacterial infections). * That follow a "ketogenic diet". * That are unable or unwilling to cooperate with either of the sample collection modes.

Design outcomes

Primary

MeasureTime frameDescription
Sensor Features Correlate with Blood Glucose Measurements1 week for the summer camp.Detection of exhaled VOC concentrations via the miniaturized laboratory device that correlate with hyper- and hypoglycemic episodes determined through finger stick and CGM data. It is anticipated that the device will be capable of noninvasively estimating blood glucose levels with approximately 30% agreement relative to CGM measurements, while accurately identifying hypo- and hyperglycemic events with greater than 85-90% sensitivity/specificity.

Secondary

MeasureTime frameDescription
GC-MS Analysis of VOCs Correlate with Blood Glucose and Sensor Data1 week for the summer camp.Specific VOCs identified through GC-MS analysis are expected to correlate not only with blood glucose levels and hypo-/hyperglycemic events, but also with extracted features of the sensor response. It is anticipated that select VOCs will exhibit statistically significant correlations (R \> 0.70) with glycemic measures and may demonstrate stronger associations with blood glucose levels and glycemic state classification compared to the metal oxide gas sensor array.

Countries

United States

Contacts

CONTACTMangilal Agarwal, PhD
agarwal@iu.edu317-278-9792
CONTACTAkanksha Tipparti, M.S.
atippart@iu.edu317-626-9725
PRINCIPAL_INVESTIGATORLinda DiMeglio, MD

Indiana University

PRINCIPAL_INVESTIGATORMark Woollam, PhD

Indiana University

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Jul 11, 2026