Wavelength selection-based nonlinear calibration for transcutaneous blood glucose sensing using Raman spectroscopy
Wavelength selection-based nonlinear calibration for transcutaneous blood glucose sensing using Raman spectroscopy
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DOI：
10.1117/1.3611006
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发表时间：
2011-08-01
影响因子：
3.5
通讯作者：
Feld, Michael S.
中科院分区：
文献类型：
--
作者：
Dingari, Narahara Chari;Barman, Ishan;Feld, Michael S.
虽然拉曼光谱学为生物样品的非侵入性和真实的诊断提供了强大的工具，但是其向临床环境的转化受到光谱校准模型的鲁棒性的缺乏以及常规实验室拉曼系统的尺寸和笨重性质的阻碍。采用全谱分析的线性多变量校正模型经常被虚假的相关性所误导，如系统漂移和组分间的协变。此外，这种校准方案易于过拟合，特别是在存在可能在光谱-浓度关系中产生非线性的外部干扰的情况下。为了解决这两个问题，我们将残差图为基础的波长选择和非线性支持向量回归（SVR）。波长选择用于消除光谱的无信息区域，而SVR用于模拟弯曲效应，例如由组织浊度和温度波动产生的弯曲效应。使用葡萄糖检测在组织幻影作为一个代表性的例子，我们表明，即使使用SVR分析的波长的数量大幅减少导致校准模型的线性全光谱分析的预测精度相当。此外，从人体受试者研究获得的临床数据集，我们还证明了所选波长子集的前瞻性适用性，而不会牺牲预测精度，这对校准维护和转移具有广泛的影响。另外，这种波长选择可以显著减少串行拉曼采集系统的收集时间。考虑到串行拉曼系统相对于传统色散拉曼光谱仪的占地面积减小，我们预计在这种硬件设计中并入波长选择将在不久的将来提高用于疾病诊断的小型化临床系统的可能性。(C)2011年，美国光电仪器工程师学会（SPIE）。[DOI 10.1117/1.3611006]
While Raman spectroscopy provides a powerful tool for noninvasive and real time diagnostics of biological samples, its translation to the clinical setting has been impeded by the lack of robustness of spectroscopic calibration models and the size and cumbersome nature of conventional laboratory Raman systems. Linear multivariate calibration models employing full spectrum analysis are often misled by spurious correlations, such as system drift and covariations among constituents. In addition, such calibration schemes are prone to overfitting, especially in the presence of external interferences that may create nonlinearities in the spectra-concentration relationship. To address both of these issues we incorporate residue error plot-based wavelength selection and nonlinear support vector regression (SVR). Wavelength selection is used to eliminate uninformative regions of the spectrum, while SVR is used to model the curved effects such as those created by tissue turbidity and temperature fluctuations. Using glucose detection in tissue phantoms as a representative example, we show that even a substantial reduction in the number of wavelengths analyzed using SVR lead to calibration models of equivalent prediction accuracy as linear full spectrum analysis. Further, with clinical datasets obtained from human subject studies, we also demonstrate the prospective applicability of the selected wavelength subsets without sacrificing prediction accuracy, which has extensive implications for calibration maintenance and transfer. Additionally, such wavelength selection could substantially reduce the collection time of serial Raman acquisition systems. Given the reduced footprint of serial Raman systems in relation to conventional dispersive Raman spectrometers, we anticipate that the incorporation of wavelength selection in such hardware designs will enhance the possibility of miniaturized clinical systems for disease diagnosis in the near future. (C) 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.3611006]