Multiscale Distribution Entropy Analysis of Short-Term Heart Rate Variability

摘要: Electrocardiogram (ECG) signal has been commonly used to analyze the complexity of heart rate variability (HRV). For this, various entropy methods have considerably interest. The multiscale (MSE) method, which makes use sample (SampEn) calculation coarse-grained time series, attracted attention for analysis HRV. However, SampEn computation may fail be defined when length a series is not enough long. Recently, distribution (DistEn) with improved stability short-term proposed. Here, we propose novel DistEn (MDE) HRV by utilizing moving-averaging process and each moving-averaged series. Thus, it provides an evaluation extracted from ECG. To verify performance MDE, employ synthetic signals confirm superiority MDE over MSE. Then, evaluate ECG congestive failure (CHF) patients healthy subjects. experimental results exhibit that capable quantifying decreased aging CHF disease