Non-Invasive Infrared-Based Measurement of Human Blood Glucose

Background and aims: Non-Invasive blood glucose monitoring using infrared (IR) light is considered a handy and reliable tool to measure blood sugar levels during daily activities. IR-based glucose monitoring principle depends on the variant absorption levels of IR light wave by blood with high or low levels of glucose solution. This paper introduces a low-cost finger probe to measure glucose based on Arduino and machine learning-based Clark error grids.

Methods: An electronic blood glucose meter is designed and implemented in a non-invasive and painless manner based on an infrared sensor. The electrical signal expressing the level of glucose in the blood with a mathematical equation is used for calibration and mapping the physical and electrical values. The final numerical value is validated with the Clark error grid by implementing fuzzy logic (FL).

Results: The designed device is tested on 30 subjects with 15 diabetes subjects. The results show a high significance of results with less than 3% of error with the reference device. The proposed method of using FL with Clark error grid gives more confident and precise output in this kind of portable device.