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Preliminary Clinical Validation of a Differential Correction Method for Improving Measurement Accuracy in Noninvasive Measurement of Blood Glucose Using Near-Infrared Spectroscopy

机译:近红外光谱法改善血糖非侵蚀性测量测量精度的差分校正方法的初步临床验证

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One of the main challenges in the noninvasive sensing of blood glucose by near-infrared (NIR) spectroscopy is the background variations from light source drift, sweating, and temperature change at the human-machine interface. In this paper, a differential correction method based on the spectra from the floating-reference position and measuring position is proposed to eliminate these spectral variations from background interferences. Its effectiveness was validated by invitro and invivo experiments in which the diffuse reflectance of intralipid solutions and human skin was collected at the source distances of 0.6mm and 2mm by the custom-built system with six super-luminescent emitting diodes (SLEDs) light source. The results showed that, for the invitro experiments of intralipid solutions, the coefficients of variations of diffuse reflectance decreased by 20.5% under all the six wavelengths after differential correction. For the invivo experiments of oral glucose tolerance tests (OGTTs), partial least squares (PLS) regression models between glucose concentrations and the diffuse reflectance from palm skin were built, and the root mean square error of cross validation (RMSECV) decreased by 38.0% on average after the differential correction. Further, the spectra of the oral water tolerance tests (OWTTs) were collected for correlation with glucose concentration in OGTTs, and their correlation coefficients (R) decreased by 35.0% on average after the differential correction. Therefore, this differential correction method based on the spectra from the floating-reference position and measuring position can weaken the influence of background variations on the NIR spectroscopy and has promising potential in invivo detection, especially for noninvasive blood glucose measurement.
机译:近红外线(NIR)光谱的血糖非侵略性感测的主要挑战之一是人机界面处的光源漂移,出汗和温度变化的背景变化。在本文中,提出了一种基于来自浮选位置和测量位置的光谱的差分校正方法,以消除背景干扰的这些光谱变化。通过invivo和Invivo实验验证其有效性,其中通过定制系统在0.6mm和2mm的源极距离下收集intralipid溶液和人体皮肤的漫反射率,具有六个超发光发射二极管(Sleds)光源。结果表明,对于intralipid溶液的invitro试验,差动校正后的所有六个波长下漫反射率的变化系数降低了20.5%。对于口腔葡萄糖耐量试验(OGTT)的Invivo实验,构建了葡萄糖浓度与来自棕榈皮肤的漫射反射之间的部分最小二乘(PLS)回归模型,并且交叉验证的根均方误差(RMSECV)降低了38.0%差动校正后平均。此外,收集口腔水耐耐受试验(OWTTS)的光谱,用于与葡萄糖浓度的术中的葡萄糖浓度相关,并且它们的相关系数(R)平均在差分校正后平均降低了35.0%。因此,基于浮动参考位置和测量位置的光谱的这种差分校正方法可以削弱NIR光谱对NIR光谱对的影响,并且在Invivo检测中具有有希望的潜力,特别是对于非侵入性血糖测量。

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