Application of denoising and background elimination based on wavelet transform to blood glucose noninvasive measurement of near infrared spectroscopy

Noises and background produced by the absorption of water in spectra signal are the main interference for prediction accuracy of quantitative calibration in blood glucose noninvasive measurement.By utilizing wavelet transform,the spectra signal can be split into multi-scale approximation and detail component.According to uninformative variable elimination(UVE) criterion,it is possible to distinguish the high-scale approximation component which presents background and low-scale detail coefficients which present noise from original spectra,and then to eliminate the corresponding component,so the background and noise can be eliminated simultaneously.In this study,the pretreatment method of wavelet transform combined with UVE criterion was applied to the research of blood glucose noninvasive measurement based on near infrared spectroscopy,and the adaptability of this pretreatment method to the uncertainty complex spectra model was also discussed.The results indicate that this pretreatment method is effective to eliminate background and noise in near infrared spectra of blood glucose noninvasive measurement.It is helpful to improve the prediction accuracy of quantitative calibration for blood glucose noninvasive measurement.