Very Selective Detection of Low Physiopathological Glucose Levels by Spontaneous Raman Spectroscopy with Univariate Data Analysis

After decades of research on non-invasive glucose monitoring, invasive devices based on finger blood sampling are still the predominant reference for diabetic patients for accurately measuring blood glucose levels. Meanwhile, research continues improving point-of-care technology toward the development of painless and more accurate devices. Raman spectroscopy is well-known as a potentially valuable and painless approach for measuring glucose levels. However, previous Raman studies deal with glucose concentrations that are still order of magnitudes away with respect to human tissues' physiological concentrations, or they propose enhancement methodologies either invasive or much complex to assure sufficient sensitivity in the physiological range. Instead, this study proposes an alternative non-enhanced Raman spectroscopy approach sensitive to glucose concentrations from 1 to 5 mmol/l, which correspond to the lowest physiopathological glucose level in human blood. Our findings suggest a very selective detection of glucose with respect to other typical metabolites, usually interfering with Raman spectroscopy's glucose detection. We validate the proposed univariate sensing methodology on glucose solutions mixed with lactate and urea, the two most common molecules found in human serum with concentrations similar to glucose and similar features in the Raman spectra. Our findings clearly illustrate that reliable detection of glucose by Raman spectroscopy is feasible by exploiting the shifted peak at 1125 +/- 10 cm(-1) within physiopathological ranges.