心率变异性数据具有非平稳和瞬时波动的特点,本文提出了采用自回归条件异方差(ARCH)分析方法分析这种波动.分析方法采用自回归移动平均模型消除序列的趋势和相关性,采用F检验法判断残差序列中是否存在ARCH效应,同时给出接受ARCH效应的概率.对充血性心衰竭病人和正常人的心率波动序列进行分析,两类人群ARCH特征接受概率及其变化率的统计值有较大差异,表明该方法可以区分不同的群体,为心电信息学研究提供了一种新的方法.
Heart rate variability (HRV) has the characteristics of non stationary and transient fluctuation. In this paper, we propose using the autoregressive conditional heteroskedasticity (ARCH) to analyze such fluctuations. Analytical methods include using auto-regressive moving average model to eliminate sequence trends and eorrelativity, using the F-test method to determine whether there is ARCH effect in residual sequence, while giving an acceptance probability of ARCH effect. The fluctuations of HRV in congestive heart failure (CHF) patients and normal people are analyzed in this paper. The large difference in statistics value of acceptance probability between CHF patients and normal people indicates that the method can well distinguish between different groups. It provides a new method for the study of ECG information.