Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720, USA.
Lab Chip. 2019 Oct 7;19(19):3179-3189. doi: 10.1039/c9lc00598f. Epub 2019 Aug 21.
Sweat sensors introduced in recent years have targeted a variety of sweat features and biomarkers for non-invasive health monitoring. Amongst these targets, reliable monitoring of sweat rate is crucial due to its modulation of sweat analyte concentrations and its intrinsic significance to numerous medical and physiological health conditions. Here we present a sweat rate sensor structure comprising of electrodes with interdigitated fingers in a microfluidic channel. Each time the accumulating sweat impinges on an electrode finger, the sensor reports a jump in admittance that can be simply and efficiently counted to estimate sweat rate, overcoming selectivity limitations of previously reported sweat rate sensors. We further integrate an impedimetric sensor for measuring total ionic charge concentration and an electrochemical Na sensor, together creating a multi-modal system for analyzing fluid and electrolyte secretion. We demonstrate how low analyte diffusion rates through this microfluidic device allow for multi-purpose sensor function, including utilizing the sweat rate sensor signal to corroborate total ionic sensor measurements. This cross-verification capability ensures data integrity in real time, satisfying a vital consideration for personalized healthcare technologies. We use the presented patch for continuous analysis of sweat rate, total ionic charge concentration, and Na concentration during exercise, while demonstrating how multi-modal cross-verification brings new trust to sensor readings.
近年来推出的汗液传感器针对各种汗液特征和生物标志物进行非侵入性健康监测。在这些目标中,由于汗液分析物浓度的调制及其对许多医学和生理健康状况的内在意义,可靠监测汗液率至关重要。在这里,我们提出了一种由微流道中的叉指电极组成的汗液率传感器结构。每次积聚的汗液冲击电极指时,传感器都会报告导纳的跃变,通过简单有效地计数即可估算出汗液率,克服了以前报道的汗液率传感器的选择性限制。我们进一步集成了一个用于测量总离子电荷浓度的阻抗传感器和一个电化学 Na 传感器,共同创建了一个用于分析流体和电解质分泌的多模态系统。我们展示了低分析物扩散速率如何通过该微流道设备实现多用途传感器功能,包括利用汗液率传感器信号来证实总离子传感器测量。这种交叉验证能力确保了实时数据完整性,满足了个性化医疗技术的重要考虑因素。我们使用提出的贴片在运动期间连续分析汗液率、总离子电荷浓度和 Na 浓度,同时展示了多模态交叉验证如何为传感器读数带来新的信任。