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Sweat biomarker analysis has attracted much interest in applications ranging from sports to wearable healthcare. Among all the sweat biomolecules, abnormal urea levels have been linked to several complications, particularly renal dysfunction. Here, we report the first application of non-enhanced (i.e., spontaneous) Raman spectroscopy for urea sensing in sweat. The proposed method eliminates the need for plasmonic surface fabrication for surface enhancement or bulky ultrashort-pulsed lasers for coherent enhancement. The exploitation of non-enhanced Raman was made possible because the concentration of urea in sweat, due to sweat physiology, is significantly higher with respect to urea concentration in blood. To demonstrate the feasibility of the proposed technique, we first identified the most intense urea Raman band. We then investigated the feasibility of the single-band integration data analysis to predict urea concentration in buffer solution. Single-band data analysis holds great promise for instrument miniaturization and facilitates the effort toward mobile and wearable photonic technologies. Next, we provided firm evidence of the high selectivity of the proposed sensing concept with human sweat in vitro. Finally, we reported successful ex vivo physiological sweat urea monitoring (with artificial eccrine perspiration, the closest mimic to true human eccrine sweat) on a porcine phantom, which mimics human skin, proving the potential of the proposed technique for in situ sweat urea analysis. We recorded an excellent linear calibration for urea concentrations from 0 to 60 mM with R2 value of 0.9973, high sensitivity of 3521 count/mM, and low detection and quantification limits of 0.47 and 1.33 mM, respectively.
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