中文摘要：

在近红外无创血糖测量中,由于人体血糖浓度变化引起的光强变化非常小,光谱易受到测量仪器以及被测对象自身生理变化的影响。背景变化的影响在测量过程中是无法消除的,只能通过有效的方法来降低这种变化带来的影响,其中选择光学性质与待测物相似,通过扣除相似参考物的光谱来修正该影响是目前常用的手段之一。为减小背景变化对光谱信号的干扰,准确地提取葡萄糖的特异性信号,提出了一种双光路测量结合净信号（NAS）处理的参考测量方法,采用双光路双检测器系统同步测量参考物和被测样品的光谱,然后基于参考物的光谱构建噪声空间计算样品光谱中的葡萄糖的净信号,并在纯吸收和强散射介质中开展了葡萄糖的建模实验,最后,结合二维相关光谱（2DCOS）分析技术和偏最小二乘回归（PLSR）模型对该方法的有效性进行了评价。二维相关分析的结果表明,与直接扣除参考背景的方式相比,净信号处理能突出葡萄糖的特异信号;而PLSR模型的预测结果表明,双光路的效果要优于单光路扣除背景光谱,糖在水溶液和20%-Intralipid溶液中的预测均方根误差（RMSEP）分别降低了35.25%和37.95%;而双光路结合净信号处理后,两种溶液的预测精度又分别提高了26.11%和14.84%。这表明,双光路测量和净信号分析相结合的方法能更有效地提取葡萄糖的特征信息,提高模型的预测精度,从而为无创血糖检测的实现提供更多可能。

英文摘要：

In the field of noninvasive blood glucose sensing by near-infrared（NIR）spectroscopy,spectra are highly susceptible to the influence of background variations caused by the measuring instruments and physiological variations from the measured object because the concentration range of glucose in blood is usually small.It should be noted that the influence of background variations cannot be entirely removed;reasonable methods should be adopted in order to reduce the consequence of background variations to an acceptable level.One of the most common methods is to select a relatively stable st and ard material which shows similar optical property to the measured objects as the reference to perform the measurement.In order to maximize the elimination effect on the influence of background variations and realize a relatively accurate extraction of the glucose concentration information,a reference measurement method combined with double-beam spectra collection and net analyte signal（NAS）processing is proposed in this article.Spectra of the measured samples and reference substances are collected simultaneously with a doublebeam double-detector measuring system.The NASs of glucose are obtained by projecting every spectrum of measured samples on the noise background subspace spanned by the spectrum of the reference substance.Experiments are conducted in pure absorption and strong scattering medium respectively.Two-dimensional correlation spectroscopy（2DCOS） and partial least squares regression（PLSR）are adopted as data processing methods to test the effectiveness of the reference measurement method.Results of 2DCOS show that the specificity of glucose concentration information in samples can be improved to a large extent by NAS processing compared to the reference subtraction method.Meanwhile,the root-mean-square error of prediction（RMSEP）of PLS model predicting glucose concentration decreases by 35.25% and 37.95% respectively in the double-beam experiment of glucose aqueous solution and 20%-intralipid soluti