Literature DB >> 1696610

Arrhythmia analysis by successive RR plotting.

T Anan1, K Sunagawa, H Araki, M Nakamura.   

Abstract

A successive RR interval plot was developed to analyze arrhythmia. The plot consisted of a set of points with the x-value of (N)th RR interval and the y-value of (N + 1)th RR interval. This method was applied in the arrhythmia analysis of Holter electrocardiograms obtained from 35 patients. In the analysis of ventricular premature contractions (VPCs) this method was useful not only in detecting VPCs but also in demonstrating coupling interval-dependent characteristics of VPCs. In the analysis of atrial fibrillation the successive RR plot enabled the authors to estimate the functional refractory period of the atrioventricular conduction. In conclusion, despite its simplicity, the successive RR plot was found to be powerful in analyzing arrhythmia. Specifically, the potential to analyze integrally the coupling interval-dependent properties of various types of arrhythmia makes it attractive as a clinical tool.

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Year:  1990        PMID: 1696610     DOI: 10.1016/0022-0736(90)90163-v

Source DB:  PubMed          Journal:  J Electrocardiol        ISSN: 0022-0736            Impact factor:   1.438


  4 in total

1.  Can analysis of heart rate variability predict arrhythmia in children with Fontan circulation?

Authors:  A Rydberg; M Karlsson; R Hörnsten; U Wiklund
Journal:  Pediatr Cardiol       Date:  2007-09-19       Impact factor: 1.655

2.  Cardiac arrhythmias imprint specific signatures on Lorenz plots.

Authors:  Hans D Esperer; Chris Esperer; Richard J Cohen
Journal:  Ann Noninvasive Electrocardiol       Date:  2008-01       Impact factor: 1.468

3.  Multiscale Entropy of the Heart Rate Variability for the Prediction of an Ischemic Stroke in Patients with Permanent Atrial Fibrillation.

Authors:  Eiichi Watanabe; Ken Kiyono; Junichiro Hayano; Yoshiharu Yamamoto; Joji Inamasu; Mayumi Yamamoto; Tomohide Ichikawa; Yoshihiro Sobue; Masehide Harada; Yukio Ozaki
Journal:  PLoS One       Date:  2015-09-01       Impact factor: 3.240

4.  Optimal length of R-R interval segment window for Lorenz plot detection of paroxysmal atrial fibrillation by machine learning.

Authors:  Masaya Kisohara; Yuto Masuda; Emi Yuda; Norihiro Ueda; Junichiro Hayano
Journal:  Biomed Eng Online       Date:  2020-06-16       Impact factor: 2.819

  4 in total

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