Effective Signal Extraction Method and Model Building in Noninvasive Detection of Blood Glucose Based on Dynamic Spectrum

In order to improve the accuracy of noninvasive detection,a new method of signal extraction from the dynamic spectrum was presented.With this method,spectrum overlap was eliminated effectively.In the model building method,principal component analysis was used to reduce the dimension of the dynamic spectral matrix,genetic algorithm and BP neural network was combined to establish mathematical model to predict the blood glucose.Experimental result shows that this method can improve the accuracy of blood glucose detection.