ESTIMATION AND ERROR ANALYSIS IN MULTIMODAL SPECTROSCOPY

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 拉曼光谱提供了有关样品组成的定量光谱信息。噪声和多个重叠成分的存在使使用拉曼峰强度进行准确定量分析的尝试变得复杂。因此，多变量分析经常被用来从拉曼光谱中提取定量信息。化学计量学分析产生的浓度不确定度通常通过与参考测量进行比较来评估。参考测量的缺点是引入了包含在参考浓度中的附加误差源。此外，在许多生物样本中，如组织，获得参考浓度并不是一帆风顺的。我们推导出了一个分析公式，它估计了线性多变量校正所预测的浓度的不确定度，适用于拉曼光谱和荧光光谱。该表达式是信噪比和模型光谱重叠的函数。第一项是目标化学物质的信噪比。它由单位浓度下感兴趣分量的积分信号(范数)和数据集中的噪声(标准差)确定。第二项描述了模型基谱中重叠的影响。光谱重叠受模型中各组分的相似性、光谱数据的分辨率和数据的光谱范围的影响。该解析式用易于量化的实验参数表示，计算简单明了。对浓度不确定度进行预测的能力对于开发和改进分析测量过程是很有价值的。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Raman spectroscopy provides quantitative spectral information about sample composition. The presence of noise and multiple overlapping components complicates attempts to use Raman peak intensities for accurate quantitative analysis. Thus, multivariate analysis is often implemented to extract quantitative information from Raman spectra. The concentration uncertainty resulting from chemometric analysis is typically assessed by comparison to a reference measurement. Reference measurements have the disadvantage of introducing an additional source of error, contained in the reference concentration. Further, in many biologic samples, such as tissue, obtaining reference concentrations is not straightforward. We have derived an analytical formula that estimates the uncertainty in concentrations predicted by linear multivariate calibration, applicable to both Raman and fluorescence spectroscopy. The expression is a function of the signal to noise ratio and the model spectral overlap. The first term is the signal to noise ratio of the target chemical. It is determined by the integrated signal (norm) of the component of interest at unit concentration and the noise (standard deviation) in the data set. The second term describes the effect of overlap in model basis spectra. The spectral overlap is affected by the similarity of the components in the model, the resolution of the spectral data, and the spectral range of the data. The analytical formula is expressed in terms of easily quantifiable experimental parameters and is straightforward to evaluate. The ability to make predictions concerning the concentration uncertainty is valuable to the process of developing and refining analytical measurements.