Application of Wavelet Transform in Fundamental Study of Measurement of Blood Glucose Concentration with Near-Infrared Spectroscopy

Because of its properties of time-frequency transform, the wavelet transform is an effective denoised method. With the pretreatment of spectra based on wavelet analysis, the spectra-to-noise ratio was greatly improved while the noise was suppressed effectively. It also improved the prediction precision and robust of the model. This method is applied to fundamental study of measurement of blood glucose concentration with spectroscopy. Experimental results show that the Root mean square error of prediction (RMSEP) of the calibration model reduces by 53% and 58% respectively. It is instructive for the study of the theory of measurement of blood glucose with spectroscopy.