Abstract:
Diabetes needs regular blood glucose monitoring to
control it. Invasive blood glucose measuring is the current gold
standard. It causes discomfort for the patient and sometimes even
infections. Researchers around the world have reported different
techniques to measure blood glucose levels non-invasively, but
a universally acceptable method with required accuracy is not
yet available. We proposed a novel approach to measure blood
glucose level non-invasively using a hybrid technique combining
Near InfraRed (NIR) absorption and bio-impedance measurements.
We tested the methods individually first. Then Artificial
Neural Network (ANN) and least squares regression were used to
integrate the two methods. The combined methods showed better
accuracy compared to the individual measurements. The hybrid
technique developed using the linear regression models showed
a superior outcome with 90% and 10% of the data points in the
regions A and B of the Clarke error grid, which are considered
acceptable.
Citation:
N. D. Nanayakkara, S. C. Munasingha and G. P. Ruwanpathirana, "Non-Invasive Blood Glucose Monitoring using a Hybrid Technique," 2018 Moratuwa Engineering Research Conference (MERCon), 2018, pp. 7-12, doi: 10.1109/MERCon.2018.8421885.