Dual Wavelength based Approach with Partial Least Square Regression for the Prediction of Glucose Concentration
Diabetes mellitus is a group of metabolic disorder characterized by high blood sugar levels. Monitoring of blood glucose levels at regular intervals plays a crucial role in the management of diabetes. The non-invasive real-time monitoring of glucose using near-infrared (NIR), Raman, acoustic and bio-impedance techniques have an edge over available invasive techniques but suffers from low Signal to Noise ratio (S/N) and other interferences. In the present work, we have attempted to improve S/N for the efficient detection of feeble signals corresponding to the physiological glucose concentrations. Investigations were carried out in the NIR region particularly from 800-1400 nm for the identification of the unique absorption features of glucose using UV-Vis NIR spectrophotometer with different ranges of glucose concentrations including 5 g/dl- 45 g/dl, 1400 mg/dl -2500 mg/dl, 35 mg/dl-650 mg/dl . Savitzky Golay (SG) pre-processing filter was applied on the raw data for enhancing the S/N for better prediction of glucose concentrations. The absorption spectra of glucose revealed the presence of a peak at 960 nm. Therefore, considering the absorbance at 960 nm, provided an enhancement in the S/N ratio from 17 dB to 27 dB. Further, partial least square regression (PLSR), has been applied on SG filtered data for a better prediction of glucose concentration with a correlation coefficient ( R2) value of 0.99 and root mean square error of prediction (RMSE) of 2.29 mg/dl. Further, based on the NIR spectral data, we have developed a measurement technique using two LED sources of 950 nm and 860 nm, and a wide detector (700 - 1100 nm) which converts obtained optical signal into voltage. It has been observed that by considering dual wavelength detection points the prediction of glucose concentration is improved. Furthermore, with increase in the test glucose concentrations, the voltage signal decreased corresponding to the 950 nm LED. This is attributed to reduced signal intensities reaching the photodiode as a result of the increase in glucose absorption. Incorporating dual wavelengths for PLSR reduced the RMSE from 8.98 mg/dl to 6.49 mg/dl and also improved the R2 value from 0.97 to 0.99.
Non-invasive, NIR spectroscopy, Savitzky Golay, Partial Least Square Regression (PLSR), Multivariate calibration
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