The Analysis Of Heart Sound Signal Based On Wavelet And Hilbert-huang Transform

Heart sound is a very important human physiological signal, which has a large number of physiological and pathological information on the various parts of the heart ventricle, atrium, great vessels. Before the cardiovascular disease, the noise in heart sound can often indicate the arrival of some heart disease. Using detecting of heart sound signal, we can find some cardiovascular disease, while using ECG can not.There is noise always in the heart sound signal. Because of the influence of noise, the signal may have serious biological signal distortion, even beyond recognition, and then lose the value of medical diagnosis. Traditional noise reduction method is low pass filter based on Fourier transform, but when the signal and noise frequency bands overlap, the effect of the method is relatively poor. Therefore, the paper introduced the wavelet transform to reduce noise in heart sound signal. Because wavelet transform in Low-frequency part has high frequency resolution and low time resolution, in High-frequency part has high time resolution and low frequency resolution, we can isolate noise from the heart sound signal easily.Fourier transform, short time Fourier transform, Winger-Ville distribution have been applied to heart sound signal, but the result achieved is not satisfactory. Such as Fourier transform and short time Fourier transform is not suitable to non-stationary signal analysis, Winger-Ville distribution creates cross-interference terms and so on. Therefore, the paper introduced the new method called Hilbert-Huang Transformation (HHT). Because of the adaptive time-frequency decomposition of HHT and eliminating the human factor, and overcoming the shortcoming of traditional methods, HHT becomes very suitable for the analysis of heart sound signal. Subsequent experimental result proved feasibility and effectiveness of HHT.