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A Fully Integrated Wearable Patch for Real-Time Sweat Glucose Monitoring toward Practical Application

Journal 2026 · IF 8.3 · 发表于 2026 年 2 月 4 日
作者: Mingpeng Yang,Chengyu Ruan,Jun Cai,Liya Ge,Grzegorz Lisak
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摘要

Sweat glucose monitoring has emerged as a promising non-invasive approach for real-time tracking of glucose dynamics, with potential applications in diabetes management and exercise-related health analytics. However, the practical deployment of wearable sweat glucose sensors remains challenged by efficient sweat collection, reliable measurement under physiological variability, sustainable power supply, and user comfort. In this study, a fully integrated wearable patch tailored for practical applications is introduced, enabling the real-time collection and measurement of glucose from micro-scale sweat. The patch integrates a paper-based microfluidic chip, an enzymatic electrochemical glucose sensor, and a Near-field communication (NFC)-enabled wireless power and data transmission module into a compact platform (5.6   cm × 3   cm). Glucose analysis can be achieved using only 25   μL of sweat within 28   s, while NFC provides a stable operating voltage of 2.9   V and real-time communication with a smartphone. The glucose sensing electrode is fabricated by electrodepositing a Prussian blue (PB)-doped poly(3,4-ethylenedioxythiophene) (PEDOT) nanocomposite, achieving a sensitivity of 6.9   nA   μM −1 and a linear detection range of 1 – 1300   μM, with reliable interference resistance and stability. Preliminary on-body tests show a positive correlation between sweat glucose data from the patch and blood glucose readings from a commercial glucose meter, indicating a similar dynamic trend. By emphasizing system-level integration, battery-free operation, modular architecture, and user-friendly deployment, this work provides an application-oriented wearable platform that facilitates the translation of sweat glucose sensing from laboratory prototypes toward practical continuous monitoring devices for diabetes management and personalized health analytics.

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