Decomposition of heartbeat time series: scaling analysis of the sign sequence

Y. Ashkenazy; Pch Ivanov; S. Havlin; C. K. Peng; Y. Yamamoto; A. L. Goldberger; H. E. Stanley

Decomposition of heartbeat time series: scaling analysis of the sign sequence

Y. Ashkenazy, Pch Ivanov, S. Havlin, C. K. Peng, Y. Yamamoto, A. L. Goldberger, H. E. Stanley

Department of Physics - at Bar-Ilan University

Research output: Contribution to journal › Conference article › peer-review

33 Scopus citations

Abstract

The cardiac interbeat (RR) increment time series can be decomposed into two sub-sequences: a magnitude series and a sign series. We show that the sign sequence, a simple binary representation of the original RR series, retains fundamental scaling properties of the original series, is robust with respect to outliers, and may provide useful information about neuroautonomic control mechanisms.

Original language	English
Pages (from-to)	139-142
Number of pages	4
Journal	Computers in Cardiology
State	Published - 2000

Funding

Funders	Funder number
National Center for Research Resources	P41RR013622

Cite this

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abstract = "The cardiac interbeat (RR) increment time series can be decomposed into two sub-sequences: a magnitude series and a sign series. We show that the sign sequence, a simple binary representation of the original RR series, retains fundamental scaling properties of the original series, is robust with respect to outliers, and may provide useful information about neuroautonomic control mechanisms.",

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AU - Ashkenazy, Y.

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AU - Yamamoto, Y.

AU - Goldberger, A. L.

AU - Stanley, H. E.

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AB - The cardiac interbeat (RR) increment time series can be decomposed into two sub-sequences: a magnitude series and a sign series. We show that the sign sequence, a simple binary representation of the original RR series, retains fundamental scaling properties of the original series, is robust with respect to outliers, and may provide useful information about neuroautonomic control mechanisms.

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JO - Computers in Cardiology

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Decomposition of heartbeat time series: scaling analysis of the sign sequence

Abstract

Funding

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