Generalized Multiscale Entropy Analysis: Application to Quantifying the Complex Volatility of Human Heartbeat Time Series
Author: Madalena D Costa1, Ary L Goldberger2
Affiliation:
1 Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA.
2 Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA; Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA 02215, USA.
Conference/Journal: Entropy (Basel)
Date published: 2015 Mar 1
Other:
Volume ID: 17 , Issue ID: 3 , Pages: 1197-1203 , Special Notes: doi: 10.3390/e17031197. , Word Count: 186
We introduce a generalization of multiscale entropy (MSE) analysis. The method is termed MSE n , where the subscript denotes the moment used to coarse-grain a time series. MSE μ , described previously, uses the mean value (first moment). Here, we focus on [Formula: see text], which uses the second moment, i.e., the variance. [Formula: see text] quantifies the dynamics of the volatility (variance) of a signal over multiple time scales. We use the method to analyze the structure of heartbeat time series. We find that the dynamics of the volatility of heartbeat time series obtained from healthy young subjects is highly complex. Furthermore, we find that the multiscale complexity of the volatility, not only the multiscale complexity of the mean heart rate, degrades with aging and pathology. The "bursty" behavior of the dynamics may be related to intermittency in energy and information flows, as part of multiscale cycles of activation and recovery. Generalized MSE may also be useful in quantifying the dynamical properties of other physiologic and of non-physiologic time series.
Keywords: aging; complexity; entropy; fractal; heart rate; multiscale entropy; nonlinear dynamics.
PMID: 27099455 PMCID: PMC4834981 DOI: 10.3390/e17031197
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