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Wearable-band type visible-near infrared optical biosensor for non-invasive blood glucose monitoring

机译:用于无创血糖监测的可穿戴式可见光近红外光学生物传感器

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摘要

Diabetes is a worldwide-serious problem that can only be delayed or prevented by a regular monitoring of blood glucose (BG) concentration level. Continuous monitoring systems allow subjects to prepare the diabetes management strategy and prevent the long-term complications diseases. Until now, most studies utilize various biofluids such as sweat, tears and saliva that have serious unresolved setback such as expensive material, sensor stability, sensor calibration and long-settling time. Therefore, we developed a novel BG sensor which is cost efficient and highly wearable with a small data acquisition time window that allow a non-invasive, long-term continuous blood glucose monitoring (CGM) system. The novel biosensor exploits a unique information of the pulsatile to continuous components of the arterial blood volume pulsation during the change of blood glucose (BG) concentration at the wrist tissue. The reflected optical signal was measured in the combine visible-near infrared (Vis-NIR) spectroscopy. An in-vivo experiment which enclosed 12 volunteers in a two-hour modified carbohydrate-rich meals reached the average correlation coefficient (R-p) between the estimated and reference BG concentration of 0.86, with the standard prediction error (SPE) of 6.16 mg/dl. Moreover, the full-day experiment was also conducted to test the reliability of the proposed sensor. Results showed that the created model in the previous day, may estimate a full-day BG concentration which was done in next day with an adequate performance.
机译:糖尿病是世界性的严重问题,只有通过定期监测血糖(BG)浓度水平才能延迟或预防。连续监测系统使受试者能够制定糖尿病管理策略并预防长期并发症疾病。到现在为止,大多数研究都利用汗液,眼泪和唾液等各种生物流体,这些流体具有严重的无法解决的挫折,例如昂贵的材料,传感器稳定性,传感器校准和稳定时间长。因此,我们开发了一种新颖的BG传感器,该传感器具有成本效益,并且具有高度可穿戴性,并且数据采集时间窗口短,从而可实现无创,长期连续血糖监测(CGM)系统。新型生物传感器在腕部组织的血糖(BG)浓度变化过程中,利用搏动性到动脉血容量脉动连续成分的独特信息。反射的光信号在组合式可见-近红外(Vis-NIR)光谱仪中测量。一项体内实验将12名志愿者围在两小时的富含碳水化合物的改良膳食中,达到了估计的BG浓度和参考BG浓度之间的平均相关系数(Rp)0.86,标准预测误差(SPE)为6.16 mg / dl 。此外,还进行了全天实验以测试所提出传感器的可靠性。结果表明,在前一天创建的模型可能会估计第二天的BG浓度,而第二天的BG浓度则具有足够的性能。

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