Zhonggang Liang, Hong Yan
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2006 Oct;23(5):981-5.
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.
提出了一种计算短期心率变异性信号分形维数的新方法。该方法基于小波变换和滤波器组。该方法的实现过程为:首先,利用小波变换从心率变异性信号中提取分形分量。其次,使用自回归模型估计分形分量的功率谱分布,并采用最小二乘法估计参数γ。最后,根据公式D = 2 - (γ - 1)/2估计心率变异性信号的分形维数。为验证所提方法的稳定性和可靠性,利用分数布朗运动模拟24个分形值为1.6的分形信号进行验证,结果表明该方法具有稳定性和可靠性。