IMPROVEMENT OF NIR RAMAN SYSTEM FOR BLOOD ANALYSIS

用于血液分析的近红外拉曼系统的改进

• 批准号: 6121233
• 负责人: TAE-WOONG KOO
• 金额: $ 0.82万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-06-01 至 2000-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6121233
• 关键词: bioengineering /biomedical engineering; biological products; biomedical equipment development; biomedical resource; diabetes mellitus; human tissue; model design /development; statistics /biometry; technology /technique

In the spectra of most biological samples, there are overlapping bands from different species. While standard multivariate calibration methods, most notably PLS, can extract individual analytes' concentrations with impressive accuracy, they cannot utilize the known spectrum of an analyte during the calibration process. We have recently developed a new calibration method called hybrid linear analysis (HLA) that incorporates the known spectrum into the calibration. Already we have seen that this method can generate equivalent or superior calibrations to PLS in predicting glucose in various media including blood serum. In our upcoming work, we will extend the application of this method to other analytes, as well as continue to explore the fundamental properties of the algorithm itself.

在大多数生物样品的光谱中，存在重叠 来自不同物种的带。 标准多变量校准 方法，尤其是 PLS，可以提取单个分析物 浓度具有令人印象深刻的准确性，他们无法利用已知的 校准过程中分析物的光谱。 我们有 最近开发了一种称为混合线性的新校准方法 分析（HLA），将已知光谱纳入 校准。 我们已经看到这个方法可以生成 在预测血糖方面与 PLS 等效或优于 PLS 的校准 各种介质，包括血清。 在接下来的工作中，我们将 将此方法的应用扩展到其他分析物，以及 继续探索算法的基本属性 本身。