Signal processing on heart rate signals using the wavelet-based contourlet transform and multifractal

This paper presents a Signal Processing method on Heart Rate Signals Using The Wavelet-based Contourlet Transform and multifractal. The method is based on the Wavelet-based Contourlet transform and filter banks. The algorithm implementation process is as follows. Firstly the Wavelet-based contourlet transform orthogonal decomposes heart rate variability signal fractal component. Power spectrum of heart rate variability signal fractal component is estimated by the self regression model. The Walker equation Yule is used to fit the fractal components of the double logarithm coordinate power spectrum, and the slope is estimated. Finally, the fractal dimension of the heart rate variability signal is estimated by formula D=2-(γ-1)/2. In order to validate the feasibility of the proposed algorithm of stability and reliability, the MIT-BIH ECG database fractal signal is verified. The results show that the algorithm is applied to calculate the heart rate variability signal fractal dimension is feasible.