激光与光电子学进展, 2019, 56(4): 041701, 网络出版: 2019-02-01
Comparison of Multi-Factor-Considered Blood Glucose Prediction Models by Near-Infrared Spectroscopy
北京信息科技大学仪器科学与光电工程学院, 北京 100192
医用光学 近红外光谱 血糖 动态光谱 支持向量机 medical optics near-infrared spectroscopy blood glucose dynamic spectrum support vector machine
Taking the blood glucose concentration as an example, the accuracy of the blood glucose measurement system is improved by means of the simultaneous incorportation of the extraction data form dynamic spectra and the influencing factors of non-measured components into the prediction model. The blood glucose prediction model is established through the support vector machine algorithm. The modeling results show that the prediction value from the multi-factor-considered model is superior to that from the non-measurement-component-considered model. The correlation coefficient of the former is 0.9627, higher by 14.23% , the root mean square error is 0.13, reduced by 43.12%, and the number of samples with a relative error in the range of 10% is higher by 8.33%, compared with those of the latter.