Electrical & Computer Engineering Department, University of California, Los Angeles, California 90095, United States.
Bioengineering Department, University of California, Los Angeles, California 90095, United States.
ACS Nano. 2024 Aug 27;18(34):23365-23379. doi: 10.1021/acsnano.4c06527. Epub 2024 Aug 13.
Optical continuous glucose monitoring (CGM) systems are emerging for personalized glucose management owing to their lower cost and prolonged durability compared to conventional electrochemical CGMs. Here, we report a computational CGM system, which integrates a biocompatible phosphorescence-based insertable biosensor and a custom-designed phosphorescence lifetime imager (PLI). This compact and cost-effective PLI is designed to capture phosphorescence lifetime images of an insertable sensor through the skin, where the lifetime of the emitted phosphorescence signal is modulated by the local concentration of glucose. Because this phosphorescence signal has a very long lifetime compared to tissue autofluorescence or excitation leakage processes, it completely bypasses these noise sources by measuring the sensor emission over several tens of microseconds after the excitation light is turned off. The lifetime images acquired through the skin are processed by neural network-based models for misalignment-tolerant inference of glucose levels, accurately revealing normal, low (hypoglycemia) and high (hyperglycemia) concentration ranges. Using a 1 mm thick skin phantom mimicking the optical properties of human skin, we performed in vitro testing of the PLI using glucose-spiked samples, yielding 88.8% inference accuracy, also showing resilience to random and unknown misalignments within a lateral distance of ∼4.7 mm with respect to the position of the insertable sensor underneath the skin phantom. Furthermore, the PLI accurately identified larger lateral misalignments beyond 5 mm, prompting user intervention for realignment. The misalignment-resilient glucose concentration inference capability of this compact and cost-effective PLI makes it an appealing wearable diagnostics tool for real-time tracking of glucose and other biomarkers.
光学连续血糖监测 (CGM) 系统由于其成本低、耐用时间长，相对于传统电化学 CGM 系统，正在成为个性化血糖管理的新兴手段。在这里，我们报告了一种计算 CGM 系统，它集成了一种生物相容性的基于磷光的可插入生物传感器和一个定制的磷光寿命成像仪 (PLI)。这种紧凑且具有成本效益的 PLI 旨在通过皮肤捕捉可插入传感器的磷光寿命图像，其中发出的磷光信号的寿命通过局部葡萄糖浓度进行调制。由于与组织自发荧光或激发泄漏过程相比，这种磷光信号的寿命非常长，因此通过在关闭激发光后测量传感器发射数十微秒的时间，可以完全避免这些噪声源。通过皮肤获得的寿命图像通过基于神经网络的模型进行处理，以进行不受错位影响的葡萄糖水平推断，准确揭示正常、低（低血糖）和高（高血糖）浓度范围。我们使用模拟人体皮肤光学特性的 1 毫米厚皮肤仿体，对 PLI 进行了体外测试，使用葡萄糖掺杂样本，得到了 88.8%的推断准确性，还显示出对皮肤仿体下方可插入传感器位置的侧向距离约为 4.7 毫米范围内的随机和未知错位的弹性。此外，PLI 还可以准确识别超过 5 毫米的较大侧向错位，并提示用户进行重新对准。这种紧凑且具有成本效益的 PLI 具有抗错位的葡萄糖浓度推断能力，使其成为实时跟踪葡萄糖和其他生物标志物的有吸引力的可穿戴诊断工具。
