微流控
可穿戴计算机
汗水
分析物
表面增强拉曼光谱
纳米技术
计算机科学
生物传感器
表面等离子共振
材料科学
拉曼光谱
化学
生物
嵌入式系统
拉曼散射
色谱法
古生物学
物理
纳米颗粒
光学
作者
Umesha Mogera,Heng Guo,Myeong Namkoong,Md. Saifur Rahman,Tan Ngoc Nguyen,Limei Tian
出处
期刊:Science Advances
[American Association for the Advancement of Science (AAAS)]
日期:2022-03-23
卷期号:8 (12)
被引量:134
标识
DOI:10.1126/sciadv.abn1736
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI