Recent advances in microelectronics, microfluidics, and electrochemical sensing platforms have enabled the development of an emerging class of fully integrated personal health monitoring devices that exploit sweat to noninvasively access biomarker information. Despite such advances, effective sweat sampling remains a significant challenge for reliable biomarker analysis, with many existing methods requiring active stimulation (e.g., iontophoresis, exercise, heat). Natural perspiration offers a suitable alternative as sweat can be collected with minimal effort on the part of the user. To leverage this phenomenon, we devised a thin hydrogel micropatch (THMP), which simultaneously serves as an interface for sweat sampling and a medium for electrochemical sensing. To characterize the performance of the THMP, caffeine and lactate were selected as two representative target molecules. We demonstrated the suitability of the sampling method to track metabolic patterns, as well as to render sample-to-answer biomarker data for personal monitoring (through coupling with an electrochemical sensing system). To inform its potential application, this biomarker sampling and sensing system is incorporated within a distributed terminal-based sensing network, which uniquely capitalizes on the fingertip as a site for simultaneous biomarker data sampling and user identification.
Keywords: Internet-of-Things; biosensor; caffeine; electrochemical analysis; hydrogel micropatch; lactate; natural perspiration; sample identification.