基于小波变换的心率变异性动态分析

Dynamic Analysis of Heart Rate Variability Based on Wavelet Transform

心率变异性(H eart rate variab ility,HRV)分析已成为无创检测心脏自主神经调节功能的一种手段。传统的频域分析,主要是计算HRV信号各频段功率,以及识别各频段的峰值频率,无论是采用经典谱估计还是AR模型都是以假设HRV信号近似平稳为前提的。这种假设在短程分析中可以基本满足,但在长程分析中,HRV信号的非平稳性便凸现出来。提出了一种基于小波变换的心率变异性动态分析方法,它不但可以获得传统的频域指标,而且可以获得它们随时间变化的动态值,称为短时功率,短时LF/HF比,特别是后者,可以动态评估自主神经活动的平衡情况。最后将这种分析方法应用到阿托品药物实验中,跟踪分析了阿托品对自主神经的影响情况。

The analysis of heart rate variability （HRV） has become a tool for noninvasively detecting the cardiovascular modulation of autonomic nervous system. Traditional analysis in frequency domain mainly includes calculating the power and detecting the peak frequency of each physiological frequency band. Whether employing the classical method or AR model to estimate the spectrum, the approximate stationarity of HRV is presupposed. Only in short term analysis can data meet this condition, while in long term the nonstationarity of HRV notably appears. A dynamic analysis method based on wavelet transform was proposed in this paper, which not only can obtain the traditional indices in frequency domain, but can compute their dynamic values varying with time, called short-time power and short-time LF/HF ratio. The latter can dynamically evaluate the activity of autonomic nervous. Finally the method was applied to trace the balance of autonomic nervous in Atropin drag experiment.