[A method to estimate the short-term fractal dimension of heart rate variability based on wavelet transform].
A new method of calculating fractal dimension of short-term heart rate variability signals is presented. The method is based on wavelet transform and filter banks. The implementation of the method is: First of all we pick-up the fractal component from HRV signals using wavelet transform. Next, we estimate the power spectrum distribution of fractal component using auto-regressive model, and we estimate parameter 7 using the least square method. Finally according to formula D = 2- (gamma-1)/2 estimate fractal dimension of HRV signal. To validate the stability and reliability of the proposed method, using fractional brown movement simulate 24 fractal signals that fractal value is 1.6 to validate, the result shows that the method has stability and reliability.
Zhonggang
Liang
L
Hong
Yan
Y
D000465:Algorithms; D004562:Electrocardiography; D005583:Fourier Analysis; D017709:Fractals; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D016018:Least-Squares Analysis; D017711:Nonlinear Dynamics; D012815:Signal Processing, Computer-Assisted