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1型糖尿病患者的无创血糖监测:一种结合用于皮肤介电和光学特性表征传感器的多传感器系统。

Non-invasive glucose monitoring in patients with Type 1 diabetes: a Multisensor system combining sensors for dielectric and optical characterisation of skin.

作者信息

Caduff Andreas, Talary Mark S, Mueller Martin, Dewarrat Francois, Klisic Jelena, Donath Marc, Heinemann Lutz, Stahel Werner A

机构信息

Solianis Monitoring AG, Leutschenbachstrasse 46, 8050 Zurich, Switzerland.

出版信息

Biosens Bioelectron. 2009 May 15;24(9):2778-84. doi: 10.1016/j.bios.2009.02.001. Epub 2009 Feb 20.

Abstract

In vivo variations of blood glucose (BG) are affecting the biophysical characteristics (e.g. dielectric and optical) of skin and underlying tissue (SAUT) at various frequencies. However, the skin impedance spectra for instance can also be affected by other factors, perturbing the glucose related information, factors such as temperature, skin moisture and sweat, blood perfusion as well as body movements affecting the sensor-skin contact. In order to be able to correct for such perturbing factors, a Multisensor system was developed including sensors to measure the identified factors. To evaluate the quality of glucose monitoring, the Multisensor was applied in 10 patients with Type 1 diabetes. Glucose was administered orally to induce hyperglycaemic excursions at two different study visits. For analysis of the sensor signals, a global multiple linear regression model was derived. The respective coefficients of the variables were determined from the sensor signals of this first study visit (R(2)=0.74, MARD=18.0%--mean absolute relative difference). The identical set of modelling coefficients of the first study visit was re-applied to the test data of the second study visit to evaluate the predictive power of the model (R(2)=0.68, MARD=27.3%). It appears as if the Multisensor together with the global linear regression model applied, allows for tracking glucose changes non-invasively in patients with diabetes without requiring new model coefficients for each visit. Confirmation of these findings in a larger study group and under less experimentally controlled conditions is required for understanding whether a global parameterisation routine is feasible.

摘要

体内血糖(BG)的变化会在不同频率下影响皮肤及皮下组织(SAUT)的生物物理特性(如介电特性和光学特性)。然而,例如皮肤阻抗谱也可能受到其他因素的影响,从而干扰与葡萄糖相关的信息,这些因素包括温度、皮肤水分和汗液、血液灌注以及影响传感器与皮肤接触的身体运动。为了能够校正这些干扰因素,开发了一种多传感器系统,该系统包括用于测量已识别因素的传感器。为了评估葡萄糖监测的质量,该多传感器应用于10名1型糖尿病患者。在两次不同的研究访视中口服葡萄糖以诱导高血糖波动。为了分析传感器信号,推导了一个全局多元线性回归模型。变量的各自系数是根据第一次研究访视的传感器信号确定的(R(2)=0.74,平均绝对相对差异MARD=18.0%)。将第一次研究访视的相同建模系数集重新应用于第二次研究访视的测试数据,以评估模型的预测能力(R(2)=0.68,MARD=27.3%)。似乎应用的多传感器与全局线性回归模型一起,能够在糖尿病患者中无创地跟踪血糖变化,而无需每次访视都使用新的模型系数。为了了解全局参数化程序是否可行,需要在更大的研究组中以及在实验控制较少的条件下对这些发现进行验证。

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