Printed microfluidic sweat sensing platform for cortisol and glucose detection. Issue 1 (9th December 2021) - Naik, Aditi R.; Zhou, Yiliang; Dey, Anita A.; Arellano, D. Leonardo González; Okoroanyanwu, Uzodinma; Secor, Ethan B.; Hersam, Mark C.; Morse, Jeffrey; Rothstein, Jonathan P.; Carter, Kenneth R.; Watkins, James J.
Abstract : An inexpensive microfluidic sweat sensor platform for single-use and continuous biomarker measurements integrated with a synthetic skin for characterization at various sweat rates. Abstract : Wearable sweat biosensors offer compelling opportunities for improved personal health monitoring and non-invasive measurements of key biomarkers. Inexpensive device fabrication methods are necessary for scalable manufacturing of portable, disposable, and flexible sweat sensors. Furthermore, real-time sweat assessment must be analyzed to validate measurement reliability at various sweating rates. Here, we demonstrate a "smart bandage" microfluidic platform for cortisol detection and continuous glucose monitoring integrated with a synthetic skin. The low-cost, laser-cut microfluidic device is composed of an adhesive-based microchannel and solution-processed electrochemical sensors fabricated from inkjet-printed graphene and silver solutions. An antibody-derived cortisol sensor achieved a limit of detection of 10 pM and included a low-voltage electrowetting valve, validating the microfluidic sensor design under typical physiological conditions. To understand effects of perspiration rate on sensor performance, a synthetic skin was developed using soft lithography to mimic human sweat pores and sweating rates. The enzymatic glucose sensor exhibited a range of 0.2 to 1.0 mM, a limit of detection of 10 μM, and reproducible response curves at flow rates of 2.0 μL min −1 and higher when integrated with the synthetic skin, validating its relevance for human health monitoring. These results demonstrate the potential of using printed microfluidic sweat sensors as a low-cost, real-time, multi-diagnostic device for human health monitoring.