Non-Invasive Glucose Monitoring for T2D via Correlated Electrolyte Concentrations

Overview

Type II Diabetes has become increasingly prevalent, with over 462 million individuals suffering from the disease worldwide. However, current glucose monitoring methods necessary for maintaining a healthy blood sugar threshold are painful, costly, and unsustainable. This project seeks to develop an alternative method through the establishment of a novel, spectrophotometrically-obtained correlation between glucose and electrolyte concentrations (potassium, sodium, and phosphate) in the blood. Silkworms were used as a diabetic model for experimentation, with different groups fed varying sugar-to-food ratios of 1:12, 1:9, and 1:6 to ensure diversity in glucose levels, as well as a 0:1 control group. Absorption values at optimal wavelengths (established in Phase 1) for each electrolyte as well as their corresponding glucose concentrations, obtained using a glucometer, were recorded from centrifuged silkworm hemolymph. Polynomial regression was employed to obtain the correlative equation relating both variables and the R2 value (correlative strength). All three electrolytes fulfilled the criteria for a strong model with R2 values exceeding 0.9, indicating high correlations between electrolytes and glucose in the hemolymph. Additionally, ANOVA tests were performed to ensure that an increase in one electrolyte concentration did not significantly correspond with another, further proving the absorbance values were collected based on electrolyte concentrations and not variable color changes. These correlative equations were applied in a functional prototype; a portable spectrophotometer that approximates glucose concentration using electrolyte absorbance obtained using a photodiode and LED lights corresponding with the absorption spectra of the electrolytes.

Competition history

• AJAS 2025 Category not listed

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