Autonomous sweat extraction and analysis applied to cystic fibrosis and glucose monitoring using a fully integrated wearable platform

Journal Article · 16 April 2017 · Proceedings of the National Academy of Sciences of the United States of America

DOI: https://doi.org/10.1073/pnas.1701740114 · OSTI ID:1351925

Emaminejad, Sam ^[1]; Gao, Wei ^[2]; Wu, Eric ^[3]; Davies, Zoe A. ^[4]; Yin Yin Nyein, Hnin ^[2]; Challa, Samyuktha ^[5]; Ryan, Sean P. ^[4]; Fahad, Hossain M. ^[2]; Chen, Kevin ^[2]; Shahpar, Ziba ^[2]; Talebi, Salmonn ^[5]; Milla, Carlos ^[6]; Javey, Ali ^[2]; Davis, Ronald W. ^[7]

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1. Stanford Genome Technology Center, Stanford School of Medicine, Palo Alto, CA 94304,, Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720,, Berkeley Sensor and Actuator Center, University of California, Berkeley, CA 94720,, Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720,
2. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720,, Berkeley Sensor and Actuator Center, University of California, Berkeley, CA 94720,, Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720,
3. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720,
4. The Stanford Cystic Fibrosis Center, Center for Excellence in Pulmonary Biology, Stanford School of Medicine, Palo Alto, CA 94305,
5. Stanford Genome Technology Center, Stanford School of Medicine, Palo Alto, CA 94304,, Department of Electrical Engineering, Stanford University, Stanford, CA 94305
6. Department of Electrical Engineering, Stanford University, Stanford, CA 94305
7. Stanford Genome Technology Center, Stanford School of Medicine, Palo Alto, CA 94304,

Significance The inherent inaccessibility of sweat in sedentary individuals in large volume (≥10 µL) for on-demand and in situ analysis has limited our ability to capitalize on this noninvasive and rich source of information. Through devising an electrochemically enhanced, programmable, and miniaturized iontophoresis interface, integrated in a wearable sensing platform, we demonstrated a method for periodic sweat extraction and in situ analysis. The system can be programmed to induce sweat with various secretion profiles, which in combination with the in situ analysis capability allow us to gain real-time insight into the sweat-secretion and gland physiology. To demonstrate the clinical value of our platform, human subject studies were performed in the context of the cystic fibrosis diagnosis and preliminary investigation of the blood/sweat glucose correlation.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: National Science Foundation (NSF); USDOE; USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
• Grant/Contract Number: AC02-05CH11231
• OSTI ID: 1351925
• Journal Information: Proceedings of the National Academy of Sciences of the United States of America, Journal Name: Proceedings of the National Academy of Sciences of the United States of America Journal Issue: 18 Vol. 114; ISSN 0027-8424
• Publisher: Proceedings of the National Academy of SciencesCopyright Statement
• Country of Publication: United States
• Language: English