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Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis

Nature volume 529, pages 509–514 (2016)Cite this article

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Abstract

Wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual’s state of health1,2,3,4,5,6,7,8,9,10,11,12. Sampling human sweat, which is rich in physiological information13, could enable non-invasive monitoring. Previously reported sweat-based and other non-invasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state14,15,16,17,18. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanically flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plastic-based sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing. This application could not have been realized using either of these technologies alone owing to their respective inherent limitations. The wearable system is used to measure the detailed sweat profile of human subjects engaged in prolonged indoor and outdoor physical activities, and to make a real-time assessment of the physiological state of the subjects. This platform enables a wide range of personalized diagnostic and physiological monitoring applications.

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Figure 1: Images and schematic illustrations of the FISA for multiplexed perspiration analysis.
Figure 2: Experimental characterizations of the wearable sensors.
Figure 3: On-body real-time perspiration analysis during stationary cycling.
Figure 4: Hydration status analysis during group outdoor running using the FISAs.

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Acknowledgements

The sensor design, characterization and testing aspects of this work were supported by the Berkeley Sensor and Actuator Center, and National Institutes of Health grant number P01 HG000205. The sensor fabrication was performed in the Electronic Materials (E-MAT) laboratory funded by the Director, Office of Science, Office of Basic Energy Sciences, Material Sciences and Engineering Division of the US Department of Energy under contract number DE-AC02-05CH11231. K.C. acknowledges funding from the NSF Nanomanufacturing Systems for mobile Computing and Energy Technologies (NASCENT) Center. H.O. acknowledges support from a Japan Society for the Promotion of Science (JSPS) Fellowship. We thank J. Bullock, C. M. Sutter-Fella, H. W. W. Nyein, Z. Shahpar, M. Zhou, E. Wu and W. Chen for their help.

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Author notes

  1. Wei Gao and Sam Emaminejad: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, 94720, California, USA

    Wei Gao, Sam Emaminejad, Hnin Yin Yin Nyein, Kevin Chen, Hossain M. Fahad, Hiroki Ota, Hiroshi Shiraki, Daisuke Kiriya, Der-Hsien Lien & Ali Javey

  2. Berkeley Sensor and Actuator Center, University of California, Berkeley, 94720, California, USA

    Wei Gao, Sam Emaminejad, Hnin Yin Yin Nyein, Kevin Chen, Hossain M. Fahad, Hiroki Ota, Hiroshi Shiraki, Daisuke Kiriya, Der-Hsien Lien & Ali Javey

  3. Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, 94720, California, USA

    Wei Gao, Sam Emaminejad, Hnin Yin Yin Nyein, Kevin Chen, Hossain M. Fahad, Hiroki Ota, Hiroshi Shiraki, Daisuke Kiriya, Der-Hsien Lien & Ali Javey

  4. Stanford Genome Technology Center, Stanford School of Medicine, Palo Alto, 94304, California, USA

    Sam Emaminejad, Samyuktha Challa & Ronald W. Davis

  5. Integrative Biology, University of California, Berkeley, 94720, California, USA

    Austin Peck & George A. Brooks

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Contributions

W.G., S.E. and A.J. conceived the idea and designed the experiments. W.G., S.E., H.Y.Y.N. and S.C. led the experiments (with assistance from K.C., A.P., H.M.F., H.O., H.S., H.O., D.K., D.-H.L.). W.G., S.E., A.P., G.A.B., R.W.D. and A.J. contributed to data analysis and interpretation. W.G., S.E., H.Y.Y.N., G.A.B. and A.J. wrote the paper and all authors provided feedback.

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Correspondence to Ali Javey.

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The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Fabrication process of the flexible sensor array.

a, PET cleaning using acetone, isopropanol and O2 plasma etching. b, Patterning of Cr/Au electrodes using photolithography, electron-beam evaporation and lift-off in acetone. c, Parylene insulating layer deposition. d, Photolithography and O2 plasma etching of parylene in the electrode areas. e, Electron-beam deposition of the Ag layer followed by lift-off in acetone. f, Ag etching on the Au working electrode area and Ag chloridation on the reference electrode area. g, Optical image of the flexible electrode array. h, Photograph of the multiplexed sensor array after surface modification.

Extended Data Figure 2 The characterizations of the modified electrodes.

a, Cyclic voltammetry of the amperometric glucose and lactate sensors using Prussian blue as a mediator in PBS (pH 7.2). Scan range, −0.2 V to 0.5 V; scan rate, 50 mV s−1. b, Potential stability of a PVB-coated Ag/AgCl electrode and a solid-state Ag/AgCl reference electrode (versus commercial aqueous Ag/AgCl electrode) in different NaCl solutions. c, d, The stability of a PVB-coated reference electrode in solutions containing 50 mM NaCl and 10 mM of different anionic (c) and cationic (d) solutions. Data recording was paused for 30 s for each solution change in b–d.

Extended Data Figure 3 The custom-developed mobile application for data display and aggregation.

a, The home page of the application after Bluetooth pairing. b, Real-time data display of sweat analyte levels as well as skin temperature during exercise. c, Real-time data progression of individual sensor. d, Available data sharing and uploading options.

Extended Data Figure 4 Schematic diagram of signal-conditioning circuit.

a–d, Signal conditioning circuits for (a) glucose, (b) lactate, (c) sodium and (d) potassium channels. VDD and VSS represent the positive and negative power supplies, respectively. LT1462 is the integrated-circuit chip part.

Extended Data Figure 5 The calibration and power delivery of the FISA.

a–d, Flexible PCB calibration for glucose (a), lactate (b), sodium (c) and potassium (d) channels. e, Power delivery diagram of the system. f, Photograph of a small rechargeable battery module used in the current work (placed next to a quarter-dollar coin for comparison). g, Representative photograph of the power delivery package inside a transparent wristband on a subject’s wrist.

Extended Data Figure 6 Reproducibility and long-term stability of the biosensors.

a–d, The reproducibility of the sodium (a), potassium (b), glucose (c) and lactate (d) sensors (eight samples for each kind of sensor). e–h, The long-term stability of the sodium (e), potassium (f), glucose (g) and lactate (h) sensors. Sensitivity is measured in millivolts per decade of concentration. The error bars represent the standard deviations of the measured data for five samples.

Extended Data Figure 7 Selectivity study for electrochemical biosensors.

a–d, The interference study for individual glucose (a), lactate (b), sodium (c) and potassium (d) sensors using an electrochemical working station. Data recording was paused for 30 s for the addition of each analyte in c and d. e, f, The real-time system-level interference study (e) and calibration plot (f) of the amperometric glucose and lactate sensor array with a shared solid-state Ag/AgCl reference electrode. g, h, The real-time interference study (g) and calibration plot (h) of the potentiometric Na+ and K+ sensor array with a shared PVB-coated reference electrode. Data recording was paused for 30 s for each solution change in e and g.

Extended Data Figure 8 Mechanical deformation study of the flexible sensors and the FPCB.

a–f, The responses of the sodium (a), potassium (b), glucose (c), lactate (d), temperature (e) sensors and of the FPCB (f) after 0, 30 and 60 cycles of bending. g–l, The responses of the sodium (g), potassium (h), glucose (i), lactate (j),and temperature (k) sensors and of the FPCB (l) during bending. The radii of curvature for the bending study of sensors and the FPCB were 1.5 cm and 3 cm, respectively. Data recording was paused for 30 s to change the conditions and settings.

Extended Data Figure 9 On-body real-time perspiration analysis during stationary cycling using the FISA on a subject’s wrist.

Conditions are as in Fig. 3c and d.

Extended Data Figure 10 Ex situ measurement of collected sweat samples using the FISA on a subject during stationary cycling at 150 W.

a, c, The ex situ results of [Na+] (a) and [K+] (c) from the sweat samples collected from the subject’s forehead without water intake (~2.5% of body weight dehydration). b, d, The ex situ results of [Na+] (b) and [K+] (d) from the sweat samples collected from the subject’s forehead with water intake (150 ml per 5 min).

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This file contains Supplementary Table 1, Supplementary Discussions for selection of the target analytes and Supplementary References. (PDF 152 kb)

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Gao, W., Emaminejad, S., Nyein, H. et al. Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature 529, 509–514 (2016). https://doi.org/10.1038/nature16521

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