AUTHOR=Gao Jianbo , Hu Jing , Liu Feiyan , Cao Yinhe 

TITLE=Multiscale entropy analysis of biological signals: a fundamental bi-scaling law

JOURNAL=Frontiers in Computational Neuroscience

VOLUME=Volume 9 - 2015

YEAR=2015

URL=https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2015.00064

DOI=10.3389/fncom.2015.00064

ISSN=1662-5188

ABSTRACT=Multiscale entropy (MSE) analysis is an interesting method for analyzing biological signals.
So far, however, few analytic results for MSE have been reported. This has severely
limited our basic understanding of MSE. To overcome this limitation, and more importantly,
to guide more fruitful applications of MSE in various areas of life sciences, we derive, for time
series with long memory, a fundamental bi-scaling law, one for the scale in the phase space,
the other for the block size used for smoothing. We illustrate the usefulness of the approach by
examining heart rate variability (HRV) data for the purpose of distinguishing healthy subjects
from patients with congestive heart failure, a life-threatening condition.
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