Entropy of Entropy: Measurement of Dynamical Complexity for Biological Systems

被引：33

作者：

Hsu, Chang Francis ^{[1
]}

Wei, Sung-Yang ^{[1
]}

Huang, Han-Ping ^{[1
]}

Hsu, Long ^{[1
]}

Chi, Sien ^{[2
]}

Peng, Chung-Kang ^{[3
]}

机构：

[1] Natl Chiao Tung Univ, Dept Electrophys, Hsinchu 30010, Taiwan

[2] Natl Chiao Tung Univ, Dept Photon, Hsinchu 30010, Taiwan

[3] Harvard Med Sch, Beth Israel Deaconess Med Ctr, Div Interdisciplinary Med & Biotechnol, Boston, MA 02215 USA

来源：

ENTROPY | 2017年 / 19卷 / 10期

关键词：

heart rate variability; biological complexity; Shannon entropy; inverted U curve; MULTISCALE; VARIABILITY; STIMULATION; BRAIN;

D O I：

10.3390/e19100550

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

Healthy systems exhibit complex dynamics on the changing of information embedded in physiologic signals on multiple time scales that can be quantified by employing multiscale entropy (MSE) analysis. Here, we propose a measure of complexity, called entropy of entropy (EoE) analysis. The analysis combines the features of MSE and an alternate measure of information, called superinformation, useful for DNA sequences. In this work, we apply the hybrid analysis to the cardiac interbeat interval time series. We find that the EoE value is significantly higher for the healthy than the pathologic groups. Particularly, short time series of 70 heart beats is sufficient for EoE analysis with an accuracy of 81% and longer series of 500 beats results in an accuracy of 90%. In addition, the EoE versus Shannon entropy plot of heart rate time series exhibits an inverted U relationship with the maximal EoE value appearing in the middle of extreme order and disorder.

引用

页数：12

共 33 条

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