NDLI: Tracking instantaneous entropy in heartbeat dynamics through inhomogeneous point-process nonlinear models

Content Provider	IEEE Xplore Digital Library
Author	Valenza, G. Citi, L. Scilingo, E.P. Barbieri, R.
Copyright Year	2014
Description	Author affiliation: Med. Sch., Neurosci. Stat. Res. Lab., Harvard Univ., Boston, MA, USA (Valenza, G.; Citi, L.; Barbieri, R.) \|\| Dept. of Inf. Eng., Univ. of Pisa, Pisa, Italy (Scilingo, E.P.)
Abstract	Measures of entropy have been proved as powerful quantifiers of complex nonlinear systems, particularly when applied to stochastic series of heartbeat dynamics. Despite the remarkable achievements obtained through standard definitions of approximate and sample entropy, a time-varying definition of entropy characterizing the physiological dynamics at each moment in time is still missing. To this extent, we propose two novel measures of entropy based on the inho-mogeneous point-process theory. The RR interval series is modeled through probability density functions (pdfs) which characterize and predict the time until the next event occurs as a function of the past history. Laguerre expansions of the Wiener-Volterra autoregressive terms account for the long-term nonlinear information. As the proposed measures of entropy are instantaneously defined through such probability functions, the proposed indices are able to provide instantaneous tracking of autonomic nervous system complexity. Of note, the distance between the time-varying phase-space vectors is calculated through the Kolmogorov-Smirnov distance of two pdfs. Experimental results, obtained from the analysis of RR interval series extracted from ten healthy subjects during stand-up tasks, suggest that the proposed entropy indices provide instantaneous tracking of the heartbeat complexity, also allowing for the definition of complexity variability indices.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	6369
Ending Page	6372
File Size	784806
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6945085
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Entropy Heart rate variability Complexity theory Physiology Nonlinear dynamical systems Standards Mathematical model
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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