昼夜节律下心率变异性信号的熵信息和谱特征

Changes of entropy and power spectrum in circadian rhythm for heart rate variability signals

生理系统产生的复杂波动信号能够反映其潜在的动力学特征.采用基本尺度熵和功率谱的方法分析24 h心率变异性信号.结果表明,心脏系统昼夜节律下生理和病理的变化伴随着变化的基本尺度熵和功率谱分布,但是对于近似熵,其变化却不明显;同时发现,基本尺度熵的变化能够反映相应的自主神经调控的变化,由于充血性心力衰竭患者迷走神经的调控被抑制,交感神经的调控占优势,所以数据中会出现更多变化的矢量模式组合,因此心力衰竭患者心率变异性信号的熵值较高;在夜间睡眠状态时,由于迷走神经的调控增强,交感神经的调控减少,所以健康人和心力衰竭患者的基本尺度熵都比白天清醒状态时产生了下降趋势.

Physiologic systems generate complex fluctuations in their output signals that reflect the underlying dynamics. In order to detect the effect of circadian rhythm for heart rate variability signals, we apply base-scale entropy method and power spectral analysis to the 24-hour heart rate variability signals. The results show that 1） such profound circadian- and pathologic-dependent changes are accompanied by changes in base-scale entropy and power spectral distribution, but by little changes in approximate entropy; 2） the circadian regulating ability of vagal nerve is clearly decreasing for congestive heart failure subjects; 3） the base-scale entropy is more sensitive than spectral analysis method to distinguishing wake/sleep states and identifying patterns generated from healthy and pathologic states, meanwhile, the base-scale entropy changes reflect corresponding changes in autonomic nerve outflow. With the suppression of vagal tone and dominance of sympathetic tone in congestive heart failure subjects, there are more variabilities in the m-words form 7t due to the trends in the data. So the higher base-scale entropy belongs to congestive heart failure subjects. With the decrease of sympathetic tone during sleep, the base-scale entropy drops in both healthy and congestive heart failure subjects. Finally, in order to further investigate the effect of series length, we calculate the base-scale entropy for different length series and find that the series length nearly has no influence on the result.