A Non-Invasive Method Applied to Measure Cholesterol and Glucose Levels

Abstract

This research aims to develop an innovative instrument to measure cholesterol and glucose levels non-invasively. The proposed model introduces the idea of measuring cholesterol and glucose levels without a blood sample or physical contact. This is accomplished using a near-infrared (NIR) and a photodiode. To improve accuracy and stability, an optical near-infrared (NIR) wristband sensor was developed to detect electrical pulses in the wrist tissue, which were then converted into values of cholesterol and blood glucose levels. There were 20 participants as clinical referrals in this study to identify invasive cholesterol and glucose levels. To achieve this goal, a mathematical model has been developed to create a non-linear equation between cholesterol and blood glucose levels. The performance of this model was assessed using square error prediction (SEP), the coefficient of determination (R2) and the Root Mean Square Error (RMSE). To determine the accuracy of this instrument, the ANOVA, T-test, and Clarke EGA analysis of variance were used in this study. The research findings demonstrated that the proposed strategy is practical to apply. Additionally, this instrument was tested on 40 participants with randomized ages between 20 and 60 years.