Multiscale base-scale entropy analysis of heart rate variability signal
应用多尺度化的基本尺度熵分析心率变异性

Multiscale base-scale entropy is introduced in this paper.We use it to analyze heart rate variability series.The results show that multiscale base-scale entropy can identify patterns generated from healthy and pathologic states, and can distinguish daytime and nighttime heartbeat time series. We also calculate the multiscale base-scale entropy of surrogate signal (phase randomized data), compare it with the entropy of atrial fibrillation signal, and find that the tends of two entropys are similar to each other, which indicates that atrial fibrillation reflects the linear characteristics of physiological signals. Multiscale base-scale entropy method has potential applications to studying a wide variety of other physiologic and physical time series data.