Using an LED Light Source Coupled With Spectral Image Analysis for Non-Invasive Glucose Detection

Glucose monitoring is critical for diabetes patients. However, invasive blood testing carries the risk of infection if wound care is not handled properly and non-invasive glucose testing devices are often bulky and not portable. Therefore, our study proposes the use of white light-emitting diode (LED) bulbs with different color temperatures as a light source. Additionally, ammonium metavanadate and sulfuric acid were used to prepare the detection solution instead of peroxidase to produce color, after which images were captured using a smartphone. The red, green, and blue (RGB) channels were then separated and converted into grayscale images. The average grayscale value changes in the images were analyzed to determine the linear relationship between glucose concentration and grayscale values, thus allowing for non-invasive quantitative glucose testing. When using a 3000K white LED bulb as the light source, the grayscale values of the RGB channels analyzed from the images exhibited a linear relationship with the glucose concentration at a 0.1–10 mM range. The regression equation for the red channel was y = −3.1184x+148.2, with a coefficient of determination (R
²
) of 0.9165, a limit of detection (LOD) of 2.27 mM, and a limit of quantification (LOQ) of 6.88 mM. The proposed method of using white LED bulbs as a detection light source combined with image analysis can be used to determine whether glucose concentrations in blood, saliva, or tears are higher than normal, providing the advantages of rapid, highly sensitive, and non-invasive testing.