Soyemi Olusola O, Landry Michelle R, Yang Ye, Idwasi Patrick O, Soller Babs R
Department of Anesthesiology, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA.
Appl Spectrosc. 2005 Feb;59(2):237-44. doi: 10.1366/0003702053085151.
The application of partial least squares (PLS) regression to visible-near-infrared (VIS-NIR) spectroscopy for modeling important blood and tissue parameters is generally complicated by the variation in skin pigmentation (melanin) across the human population. An orthogonal correction method for removing the influence of skin pigmentation has been demonstrated in diffuse reflectance spectra from two-layer tissue-mimicking phantoms. The absorption properties of the phantoms were defined by lyophilized human hemoglobin (bottom layer) and synthetic melanin (top layer). Tissue-like scattering was simulated in both layers with intralipid. The approach uses principal components analysis (PCA) loading vectors from a separate set of phantom spectra that encode the unwanted melanin variation to remove the effect of melanin from the test phantoms. The preprocessing of phantom spectra using this orthogonal correction method resulted in PLS models with reduced complexity and enhanced prediction performance. Preliminary results from a separate study that evaluates the feasibility of defining skin color variation in an experiment with a single human subject are also presented.
将偏最小二乘（PLS）回归应用于可见-近红外（VIS-NIR）光谱以对重要的血液和组织参数进行建模，通常会因人群中皮肤色素沉着（黑色素）的变化而变得复杂。一种用于消除皮肤色素沉着影响的正交校正方法已在来自两层组织模拟体模的漫反射光谱中得到验证。体模的吸收特性由冻干的人血红蛋白（底层）和合成黑色素（顶层）定义。两层均使用脂质乳剂模拟组织样散射。该方法使用来自一组单独的体模光谱的主成分分析（PCA）加载向量，这些向量编码了不需要的黑色素变化，以消除测试体模中黑色素的影响。使用这种正交校正方法对体模光谱进行预处理，得到了复杂度降低且预测性能增强的PLS模型。还展示了另一项单独研究的初步结果，该研究评估了在单个人体受试者实验中定义肤色变化的可行性。
