Issue 1, 2022

Printed microfluidic sweat sensing platform for cortisol and glucose detection

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.

Graphical abstract: Printed microfluidic sweat sensing platform for cortisol and glucose detection

Supplementary files

Article information

Article type
Paper
Submitted
17 Jul 2021
Accepted
12 Nov 2021
First published
09 Dec 2021

Lab Chip, 2022,22, 156-169

Author version available

Printed microfluidic sweat sensing platform for cortisol and glucose detection

A. R. Naik, Y. Zhou, A. A. Dey, D. L. G. Arellano, U. Okoroanyanwu, E. B. Secor, M. C. Hersam, J. Morse, J. P. Rothstein, K. R. Carter and J. J. Watkins, Lab Chip, 2022, 22, 156 DOI: 10.1039/D1LC00633A

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