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Wearable, nanofiber-based microfluidic systems with integrated electrochemical and colorimetric sensing arrays for multiplex sweat analysis

多路复用 微流控 汗水 可穿戴计算机 纳米技术 纳米纤维 化学 材料科学 计算机科学 嵌入式系统 生物信息学 医学 生物 内科学
作者
Xuecui Mei,Jiao Yang,Jiang Liu,Yingchun Li
出处
期刊:Chemical Engineering Journal [Elsevier]
卷期号:454: 140248-140248 被引量:22
标识
DOI:10.1016/j.cej.2022.140248
摘要

• We report a novel nanofiber-based microfluidic system for in situ sweat analysis. • Nanofibers are essential in sweat collection and reagent immobilization. • Electrochemical and colorimetric arrays were integrated in the system. • Simultaneous detection of glucose, lactate, pH, Cl − and urea was realized. • Key parts were made by simple techniques of electrospinning and direct writing. Wearable microfluidic sensors for sweat analysis are highly desirable for noninvasive monitoring of human health. However, previously reported hollow-structured microfluidic networks for sweat analysis have difficulty in avoiding the potential chemical harm to skin due to diffusion of soluble chemical reagents and cannot minimize the impairment of sensors caused by contaminants secreted from skin. Low-cost microfluidic sensors using alternative techniques are also required to enable inexpensive devices. Besides, incorporating multimodal sensors into one microfluidic device while maintaining its flexibility and miniaturization still possesses challenges. Herein, we reported a nanofiber-based microfluidic analysis system (NFMAS) for in situ sweat monitoring. Nanofibers served as the key element for microfluidic networks construction to spontaneously capture and route sweat. Dual-mode sensing arrays were embedded into the microfluidic network to protect each sensing unit from any disturbance. The NFMAS can conformally and innocuously bond to the skin surface and exhibited good performance in simultaneous quantification of glucose, lactate, pH, Cl − and urea by both electrochemistry and colorimetry modes. Human studies demonstrated that the NFMAS can provide continuous, multimodal information associated with sweat chemistry during physical exercise, revealing promising applications in real-time monitoring of human health.
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