Department Nanoengineering, University of California San Diego, La Jolla, California 92093, United States.
ACS Sens. 2021 May 28;6(5):1875-1883. doi: 10.1021/acssensors.1c00139. Epub 2021 Apr 19.
Diabetes prevalence has been rising exponentially, increasing the need for reliable noninvasive approaches for glucose monitoring. Different biofluids have been explored recently for replacing current blood finger-stick glucose strips with noninvasive painless sensing devices. While sweat has received considerable attention, there are mixed reports on correlating the sweat results with blood glucose levels. Here, we demonstrate a new rapid and reliable approach that combines a simple touch-based fingertip sweat electrochemical sensor with a new algorithm that addresses for personal variations toward the accurate estimate of blood glucose concentrations. The new painless and simple glucose self-testing protocol leverages the fast sweat rate on the fingertip for rapid assays of natural perspiration, without any sweat stimulation, along with the personalized sweat-response-to-blood concentration translation. A reliable estimate of the blood glucose sensing concentrations can thus be realized through a simple one-time personal precalibration. Such system training leads to a substantially improved accuracy with a Pearson correlation coefficient higher than 0.95, along with an overall mean absolute relative difference of 7.79%, with 100% paired points residing in the A + B region of the Clarke error grid. The speed and simplicity of the touch-based blood-free fingertip sweat assay, and the elimination of periodic blood calibrations, should lead to frequent self-testing of glucose and enhanced patient compliance toward the improved management of diabetes.
糖尿病的患病率呈指数级增长，因此需要可靠的非侵入性方法来监测血糖。最近，人们已经探索了不同的生物流体，以用非侵入性无痛感的传感设备替代当前的血液手指刺葡萄糖条。虽然汗液受到了相当多的关注，但关于汗液结果与血糖水平的相关性仍存在一些相互矛盾的报告。在这里，我们展示了一种新的快速可靠的方法，该方法结合了一种简单的基于触摸的指尖汗液电化学传感器和一种新算法，该算法解决了个人差异问题，从而能够准确估计血糖浓度。这种新的无痛、简单的葡萄糖自我检测方案利用指尖的快速出汗率来快速检测自然出汗，无需任何汗液刺激，并结合了个性化的汗液-血液浓度转换。因此，通过简单的一次性个人预校准，就可以实现对血糖传感浓度的可靠估计。通过这种系统训练，可以实现显著提高的准确性，Pearson 相关系数高于 0.95，总体平均绝对相对差异为 7.79%，100%的配对点位于 Clarke 误差网格的 A + B 区域。基于触摸的无血指尖汗液检测的速度和简单性，以及消除定期的血液校准，应该会导致频繁的自我血糖检测，从而提高患者对糖尿病管理的依从性。
