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通过近红外透射光谱法对人体舌头进行无创血糖测量。

Noninvasive blood glucose measurements by near-infrared transmission spectroscopy across human tongues.

作者信息

Burmeister J J, Arnold M A, Small G W

机构信息

Department of Chemistry and Optical Science and Technology Center, University of Iowa, Iowa City 52242, USA.

出版信息

Diabetes Technol Ther. 2000 Spring;2(1):5-16. doi: 10.1089/152091500316683.

Abstract

Noninvasive blood glucose measurements are characterized in human subjects. A series of first overtone transmission spectra are collected across the tongues of five human subjects with type 1 diabetes. The noninvasive human spectra are collected by an experimental protocol that is designed to minimize chance correlations with blood glucose levels. In one treatment of the data, every fifth sample is used as a blind prediction point to validate model performance. In another rearrangement of the data, the spectra collected over the first 29 days are used to build calibration models that are then used to predict in vivo glycemia from spectra collected over the next 10 days. Of the five data sets (one for each subject), one demonstrates a complete inability to predict blood glucose levels and is deemed void of glucose-specific information. Glucose-specific information is evident in the remaining four data sets, albeit to varying degrees. For all data sets, the ability to measure glucose from spectra collected noninvasively from human subjects depends on spectral quality and reproducibility of the tongue-to-spectrometer interface. The standard error of prediction is 3.4 mM for the best calibration model. The significance of this magnitude of prediction error is discussed relative to the situations where: (1) the model is completely void of glucose-specific information and (2) glucose predictions are limited by spectral signal-to-noise and sample thickness. Overall, glucose-specific information is available from noninvasive first-overtone spectra collected across human tongues. Significant improvements are necessary, however, before clinically useful measurements are possible.

摘要

对人体受试者的无创血糖测量进行了表征。收集了五名1型糖尿病患者舌头的一系列一次泛音透射光谱。无创人体光谱通过一种实验方案收集,该方案旨在尽量减少与血糖水平的偶然相关性。在一种数据处理方法中,每五个样本用作一个盲预测点以验证模型性能。在另一种数据重排中,前29天收集的光谱用于建立校准模型,然后用于根据接下来10天收集的光谱预测体内血糖水平。在五个数据集(每个受试者一个)中,有一个完全无法预测血糖水平,被认为没有葡萄糖特异性信息。葡萄糖特异性信息在其余四个数据集中很明显,尽管程度不同。对于所有数据集,从人体受试者无创收集的光谱测量葡萄糖的能力取决于光谱质量和舌头与光谱仪接口的可重复性。最佳校准模型的预测标准误差为3.4 mM。相对于以下情况讨论了这种预测误差幅度的意义:(1)模型完全没有葡萄糖特异性信息;(2)葡萄糖预测受光谱信噪比和样品厚度的限制。总体而言,从人体舌头收集的无创一次泛音光谱中可获得葡萄糖特异性信息。然而,在进行临床有用的测量之前,还需要显著改进。

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