应用Hilbert变换提取拉曼光谱相位信息进行血液识别分类方法的研究  

The Identification Method of Blood by Applying Hilbert Transform to Extract Phase Information of Raman Spectra

作　　者：王宁 王驰 卞海溢 王钧[3] 王鹏[2] 白鹏利[3] 尹焕才[3] 田玉冰[2] 高静[2] WANG Ning;WANG Chi;BIAN Hai-yi;WANG Jun;WANG Peng;BAI Peng-li;YIN Huan-cai;TIAN Yu-bing;GAO Jing(School of Mechatronic Engineering and Automation,Shanghai University,Shanghai 200072,China;Jiangsu Key Laboratory of Medical Optics,Suzhou Institute of Biomedical Engineering and Technology,Chinese Academy of Sciences,Suzhou 215163,China;CAS Key Lab of Bio-Medical Diagnostics,Suzhou Institute of Biomedical Engineering and Technology,Chinese Academy of Sciences,Suzhou 215163,China)

机构地区：[1]上海大学机电工程及自动化学院,上海200072 [2]中国科学院苏州生物医学工程技术研究所江苏省医用光学重点实验室,江苏苏州215163 [3]中国科学院苏州生物医学工程技术研究所中国科学院生物医学检验技术重点实验室,江苏苏州215163

出　　处：《光谱学与光谱分析》2018年第8期2412-2418,共7页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(61405236;61773249);国家(863)计划项目(2015AA021105);国家重点研发计划(2016YFB0402202);江苏省重点研发计划项目(BE2016090;BE2016005-2);江苏省博士后基金项目(1188004004)资助

摘　　要：将拉曼光谱技术和化学计量学方法相结合实现了对人血和动物血种属的区分,并提出了一种基于Hilbert变换的拉曼光谱相位提取方法,提高了人血与动物血区分的准确度。分别对血液光谱数据和它所对应的相位信息进行主成分分析(PCA),通过主成分得分图比较两者对人与动物血液的区分程度,并建立偏最小二乘判别分析(PLS-DA)模型,通过设置合适的分类阈值y,可以实现人与动物血液的有效区分。结果表明在选取第一、第二主成分分析时,利用光谱数据相位信息建立的PCA模型,识别率更高,人与动物血液明显区分开来。其所对应的PLS-DA模型最优主成分数为3,预测标准误差(RMSEP)和决定系数(R2)分别为0.044 3和0.993 2。而用血液原始光谱建立的PLS-DA模型最优主成分数为6,RMSEP和R2分别为0.053 7和0.990 1。说明利用拉曼光谱相位信息建立的PLS-DA模型可以拟合较少的主成分数来获得误差更小的预测结果。进一步观察PLS-DA模型拟合不同主成分数的预测标准误差曲线图,当选取同样多的拟合主成分数时,利用血液拉曼光谱相位信息建立的PLS-DA模型其所对应的预测标准误差均低于原始血液光谱数据。所以,通过提取血液拉曼光谱数据的相位信息,可以降低模型的复杂程度,提高识别准确度。A novel method is reported to discriminate human and animal blood by using Raman chemometric analysis. The phase information of Raman spectra was extracted with Hilbert transform and then analyzed with PCA and PLS to improve the accuracy of identification of human and animal blood compared with original spectra. The cluster analysis was made according to the principal component scores scatter plots of blood spectra data or its corresponding phase information. And the appropriate threshold value was set in the PLS-DA model in order to discriminate human and animal blood. The results show that the PCA model of the phase information can identify animal blood and human blood obviously and it exhibits higher recognition rate compared with PCA of original Raman spectra. The PLS-DA indicates that the optimal number of principal components for the phase information is 3, RMSEP and R2 are 0.044 3, 0.993 2, respectively. However, in the PLS model established with the original spectra, the optimal number of principal components is 6, RMSEP and R2 are 0.053 7, 0.990 1, respectively. This indicates that the PLS-DA model of the phase information can make less error by using less principal components. The RMSEP of PLS-DA model built by the phase information of Raman spectra is lower than that of the blood Raman spectra when taking the same number of fitting principal components. In conclusion, the complexity of the PCA and PLS models can be reduced and the recognition accuracy can be improved by extracting the phase information of Raman spectroscopy.

关 键 词：拉曼光谱技术 化学计量学方法 血液 相位信息 

分 类 号：O657.3[理学—分析化学]