Diabetes prevalence has been rising exponentially, increasing the need for reliable noninvasive approaches for glucose monitoring. Different biofluids have been explored recently for replacing current blood finger-stick glucose strips with noninvasive painless sensing devices. While sweat has received considerable attention, there are mixed reports on correlating the sweat results with blood glucose levels. Here, we demonstrate a new rapid and reliable approach that combines a simple touch-based fingertip sweat electrochemical sensor with a new algorithm that addresses for personal variations toward the accurate estimate of blood glucose concentrations. The new painless and simple glucose self-testing protocol leverages the fast sweat rate on the fingertip for rapid assays of natural perspiration, without any sweat stimulation, along with the personalized sweat-response-to-blood concentration translation. A reliable estimate of the blood glucose sensing concentrations can thus be realized through a simple one-time personal precalibration. Such system training leads to a substantially improved accuracy with a Pearson correlation coefficient higher than 0.95, along with an overall mean absolute relative difference of 7.79%, with 100% paired points residing in the A + B region of the Clarke error grid. The speed and simplicity of the touch-based blood-free fingertip sweat assay, and the elimination of periodic blood calibrations, should lead to frequent self-testing of glucose and enhanced patient compliance toward the improved management of diabetes.
Keywords: diabetes; fingertip touch sensor; noninvasive glucose analysis; personalized calibration; sweat glucose.