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      Wearable plasmonic paper–based microfluidics for continuous sweat analysis

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          Abstract

          Wearable sweat sensors have the potential to provide clinically meaningful information associated with the health and disease states of individuals. Current sensors mainly rely on enzymes and antibodies as biorecognition elements to achieve specific quantification of metabolite and stress biomarkers in sweat. However, enzymes and antibodies are prone to degrade over time, compromising the sensor performance. Here, we introduce a wearable plasmonic paper–based microfluidic system for continuous and simultaneous quantitative analysis of sweat loss, sweat rate, and metabolites in sweat. Plasmonic sensors based on label-free surface-enhanced Raman spectroscopy (SERS) can provide chemical “fingerprint” information for analyte identification. We demonstrate the sensitive detection and quantification of uric acid in sweat at physiological and pathological concentrations. The well-defined flow characteristics of paper microfluidic devices enable accurate quantification of sweat loss and sweat rate. The wearable plasmonic device is soft, flexible, and stretchable, which can robustly interface with the skin without inducing chemical or physical irritation.

          Abstract

          Abstract

          A wearable plasmonic microfluidic device enables continuous quantification of sweat loss, sweat rate, and metabolites.

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          Most cited references60

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          Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis.

          Wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual's state of health. Sampling human sweat, which is rich in physiological information, 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 state. 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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            Wearable biosensors for healthcare monitoring

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              The Dynamics of Capillary Flow

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: Writing - original draft
                Role: ConceptualizationRole: InvestigationRole: Methodology
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: SoftwareRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing
                Role: Formal analysisRole: InvestigationRole: Project administrationRole: ValidationRole: Writing - review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing
                Journal
                Sci Adv
                Sci Adv
                sciadv
                advances
                Science Advances
                American Association for the Advancement of Science
                2375-2548
                March 2022
                23 March 2022
                : 8
                : 12
                : eabn1736
                Affiliations
                [1]Department of Biomedical Engineering, Center for Remote Health Technologies and Systems, Texas A&M University, College Station, TX 77843, USA.
                Author notes
                [* ]Corresponding author. Email: ltian@ 123456tamu.edu
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-6527-8906
                https://orcid.org/0000-0002-7493-3773
                https://orcid.org/0000-0002-9209-7721
                https://orcid.org/0000-0003-0726-2399
                https://orcid.org/0000-0003-1626-4628
                https://orcid.org/0000-0002-1931-8567
                Article
                abn1736
                10.1126/sciadv.abn1736
                8942375
                35319971
                dcd30616-09e9-4f71-9c75-5ed99c71fc20
                Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

                This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 16 November 2021
                : 31 January 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: 1648451
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: 1R21EB029064-01A1
                Funded by: FundRef http://dx.doi.org/10.13039/100007904, Texas A and M University;
                Categories
                Research Article
                Physical and Materials Sciences
                SciAdv r-articles
                Materials Science
                Applied Sciences and Engineering
                Applied Sciences and Engineering
                Custom metadata
                Lou Notario

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