一种改进的小波基线校正方法的研究  

Study on a modified baseline correction method based on wavelet transform

作　　者：李庆波[1] 徐玉坡[1] 李响[1] 张广军[1] 

机构地区：[1]北京航空航天大学仪器科学与光电工程学院精密光机电一体化技术教育部重点实验室,北京100191

出　　处：《光电子．激光》2009年第5期698-701,共4页Journal of Optoelectronics·Laser

基　　金：国家自然科学基金资助项目(60708026);北京市优秀人才培养资助项目(20081D1600600348);教育部创新团队发展计划资助项目(IRT0705)

摘　　要：通过对小波变换基线校正中最佳分解尺度方法的研究,提出了一种新的基于小波变换的最佳分解尺度确定方法,不但有效地提高了基线校正效果,而且具有简单、快速的优点。将该方法应用于血糖光谱数据预处理中进行基线校正,取得了较好的效果。通过人体口服葡萄糖耐量试验(OGTT)得到人体无创检测近红外光谱和对应血糖浓度值,然后采用该方法对上述光谱进行基线校正并建立多元回归模型,采用交互验证的方式对模型及基线校正的效果进行了评价。实验结果表明,血糖浓度预测值和参考值间的相关系数为0.75,预测均方根误差(RMSEP)为1.36mmol/L,与原始光谱预测结果和其他小波分解尺度下的预测结果相比,RMSEP降低了将近39%,相关系数提高了0.64,预测精度得到较大幅度提高。A modified baseline correction method based on wavelet transform is investigated and applied to the human blood glucose non-invasive measurement. The selection method of optimum decomposition level using wavelet transform is researched,and a new method to determine the optimum decomposition level is proposed which is simple, fast, and it can effectively improve the result of baseline correction based on wavelet transform. The spectra of human finger skin and the corresponding blood glucose value are measured in human oral glucose tolerance test （OGTT） which can make the concentration of human blood glucose vary in a certain range in a short time. A regression model is established and evaluated by cross validation method. The correlation coefficient between prediction value and true value is 0. 75 ,and the root mean square error of prediction is 1.36 mmol/L. The prediction accuracy of calibration model with this modified baseline correction method is greatly improved compared with the predictions of the original spectra and the corrected spectra at other decomposition level, the root mean square error approx- imately decreases by 39% ,and the correlation coefficient increases by 0. 64.

关 键 词：基线校正 小波变换 分解尺度 血糖 红外光谱 

分 类 号：O657.33[理学—分析化学]