Booth Id:
ENBM082T
Category:
Biomedical Engineering
Year:
2025
Finalist Names:
Striek, Dylan (School: Hopkinton High School)
Nair, Anoushka (School: Hopkinton High School)
Abstract:
Over 462 million individuals suffer from Type II Diabetes worldwide. However, current glucose monitors are painful, costly, and unsustainable. This project establishes a novel, non-invasive monitor that uses the spectrophotometric detection of glucose biomarkers (potassium, sodium, and phosphate) to estimate blood sugar through the finger at wavelengths of 400-800 nm. This uniquely deviates from other spectroscopic monitors that measure glucose directly, requiring inaccessible equipment emitting wavelengths exceeding 1000 nm.
Our previous research encompassed 250+ experiments involving the induction of varying levels of diabetes in an invertebrate model, extraction of hemolytic fluid (blood equivalent), and the development of a novel prediction model effectively correlating potassium, sodium, and phosphate to glucose (R^2 > 0.9 for all three electrolytes).
This translational model was integrated into the GlycoCharge, a novel prototype. It consists of three distinct LEDs to measure the absorbances of each of the electrolytes (766.5nm, 595nm, and 470nm), a potential fourth LED to measure path length (650nm) as used in Beer's Law, an Arduino microcontroller, and a photodiode to measure transmittance.
To verify the prototype glucose output, 100 trials were conducted by comparing readings from a medically verified glucometer to the GlycoCharge device. Residual graphs and error charts yielded p > 0.001, indicating that the error associated with the GlycoCharge had no influence from outside factors and that there was a significant increase in accuracy when detecting lower glucose levels. Comparatively, a majority of current glucometers fail to measure lower extremes of glucose concentrations. The overall error for the device is 4.57%, on par with current standards.
Awards Won: