Independence and symbolic independence of nonstationary heartbeat series during atrial fibrillation

Camillo Cammarota and Enrico Rogora

Physica A: Statistical Mechanics and its Applications, 2005, vol. 353, issue C, 323-335

Abstract: Heartbeat intervals during atrial fibrillation are commonly believed to form a series of almost independent variables. The series extracted from 24h Holter recordings show a nonstationary behavior. Because of nonstationarity it is difficult to give a quantitative measure of independence. In this paper, we use and compare two methods for this. The first is a classical method which models a nonstationary series using a linear Gaussian state space model. In this framework, the independence is tested on the stationary sequence of the residuals. The second method codes data into permutations and tests the uniformity of their distribution. This test assumes as null hypothesis a weaker form of independence which we call symbolic independence. We discuss some advantages of symbolic independence in the context of heartbeat series. We analyze the time series of heartbeat intervals from 24h Holter recordings of nine subjects with chronic atrial fibrillation and find that the detrended series is a zero or one memory process for 83% of regular segments and is symbolically independent for 93% of segments.

Keywords: Nonstationary time series; State space model; Symbolic dynamics; Independence test; Holter analysis; Atrial fibrillation (search for similar items in EconPapers)
Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437105000774
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:353:y:2005:i:c:p:323-335

DOI: 10.1016/j.physa.2005.01.030

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().