Sweat sensing may provide a noninvasive means of estimating blood biomarker levels if a number of technological hurdles can be overcome. This report describes progress on a physiologically based transport model relating sweat glucose and key electrolyte concentrations to those in blood. Iontophoretically stimulated sweat glucose and fasted blood glucose were simultaneously measured in 2 healthy human subjects. Sweat glucose was measured with a novel, prototype skin sweat collection/analysis system and blood glucose with a commercial fingerstick glucometer. These data, in combination with data from 3 published studies, were used to calibrate a dynamic mathematical model for glucose transport and uptake in human skin, followed by extraction into sweat. Model simulations revealed that experimental and literature sweat glucose values were well represented under varying physiologic conditions. The glucose model, calibrated under a variety of experimental conditions including electrical enhancement, revealed a 10 min blood-to-sweat lag time and a sweat/blood glucose level ranging from 0.001 to 0.02, depending on the sweat rate. These values are consistent with those reported in the literature. The developed model satisfactorily described the sweat-to-blood relationship for glucose concentrations measured under different conditions in 4 human studies including the present pilot study. The algorithm may be used to facilitate sweat biosensor development.
Keywords: biomarkers; glucose; mathematical model; sensor; sweat.
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