汗水
微流控
材料科学
生物医学工程
纳米技术
计算机科学
工程类
海洋学
地质学
作者
Jungil Choi,Amay Jairaj Bandodkar,Jonathan T. Reeder,Tyler R. Ray,Amelia Turnquist,Sung Bong Kim,Nathaniel Nyberg,Aurélie Hourlier‐Fargette,Jeffrey B. Model,Alexander J. Aranyosi,Shuai Xu,Roozbeh Ghaffari,John A. Rogers
出处
期刊:ACS Sensors
[American Chemical Society]
日期:2019-02-01
卷期号:4 (2): 379-388
被引量:365
标识
DOI:10.1021/acssensors.8b01218
摘要
Real-time measurements of the total loss of sweat, the rate of sweating, the temperature of sweat, and the concentrations of electrolytes and metabolites in sweat can provide important insights into human physiology. Conventional methods use manual collection processes (e.g., absorbent pads) to determine sweat loss and lab-based instrumentation to analyze its chemical composition. Although such schemes can yield accurate data, they cannot be used outside of laboratories or clinics. Recently reported wearable electrochemical devices for sweat sensing bypass these limitations, but they typically involve on-board electronics, electrodes, and/or batteries for measurement, signal processing, and wireless transmission, without direct means for measuring sweat loss or capturing and storing small volumes of sweat. Alternative approaches exploit soft, skin-integrated microfluidic systems for collection and colorimetric chemical techniques for analysis. Here, we present the most advanced platforms of this type, in which optimized chemistries, microfluidic designs, and device layouts enable accurate assessments not only of total loss of sweat and sweat rate but also of quantitatively accurate values of the pH and temperature of sweat, and of the concentrations of chloride, glucose, and lactate across physiologically relevant ranges. Color calibration markings integrated into a graphics overlayer allow precise readout by digital image analysis, applicable in various lighting conditions. Field studies conducted on healthy volunteers demonstrate the full capabilities in measuring sweat loss/rate and analyzing multiple sweat biomarkers and temperature, with performance that quantitatively matches that of conventional lab-based measurement systems.
科研通智能强力驱动
Strongly Powered by AbleSci AI