A high-temporal resolution algorithm for quantifying organization during atrial fibrillation

Haris J. Sih, Douglas P. Zipes, Edward J. Berbari, Jeffrey E. Olgin

Research output: Contribution to journalArticle

99 Citations (Scopus)

Abstract

Atrial fibrillation (AF) has been described as a 'random' or 'chaotic' rhythm. Evidence suggests that AF may have transient episodes of temporal and spatial organization. We introduce a new algorithm that quantifies AF organization by the mean-squared error (MSE) in the linear prediction between two cardiac electrograms. This algorithm calculates organization at a finer temporal resolution (~300 ms) than previously published algorithms. Using canine atrial epicardial mapping data, we verified that the MSE algorithm showed nonfibrillatory rhythms to be significantly more organized than fibrillatory rhythms (p < .00001). Further, we compared the sensitivity of MSE to that of two previously published algorithms by analyzing AF with simulated noise and AF manipulated with vagal stimulation or by adenosine administration to alter the character of the AF. MSE performed favorably in the presence of noise. While all three algorithms distinguished between low and high vagal AF, MSE was the most sensitive in its discrimination. Only MSE could distinguish baseline AF from AF with adenosine. We conclude that our algorithm can distinguish different levels of organization during AF with a greater temporal resolution and sensitivity than previously described algorithms. This algorithm could lead to new ways of analyzing and understanding AF as well as improved techniques in AF therapy.

Original languageEnglish
Pages (from-to)440-450
Number of pages11
JournalIEEE Transactions on Biomedical Engineering
Volume46
Issue number4
DOIs
StatePublished - 1999

Keywords

  • Adaptive filtering
  • Atrial fibrillation (AF)
  • Signal processing
  • Tachyarrhythmia organization

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

A high-temporal resolution algorithm for quantifying organization during atrial fibrillation. / Sih, Haris J.; Zipes, Douglas P.; Berbari, Edward J.; Olgin, Jeffrey E.

In: IEEE Transactions on Biomedical Engineering, Vol. 46, No. 4, 1999, p. 440-450.

Research output: Contribution to journalArticle

Sih, Haris J. ; Zipes, Douglas P. ; Berbari, Edward J. ; Olgin, Jeffrey E. / A high-temporal resolution algorithm for quantifying organization during atrial fibrillation. In: IEEE Transactions on Biomedical Engineering. 1999 ; Vol. 46, No. 4. pp. 440-450.
@article{a6837712f6c94edf94a515e08aae741a,
title = "A high-temporal resolution algorithm for quantifying organization during atrial fibrillation",
abstract = "Atrial fibrillation (AF) has been described as a 'random' or 'chaotic' rhythm. Evidence suggests that AF may have transient episodes of temporal and spatial organization. We introduce a new algorithm that quantifies AF organization by the mean-squared error (MSE) in the linear prediction between two cardiac electrograms. This algorithm calculates organization at a finer temporal resolution (~300 ms) than previously published algorithms. Using canine atrial epicardial mapping data, we verified that the MSE algorithm showed nonfibrillatory rhythms to be significantly more organized than fibrillatory rhythms (p < .00001). Further, we compared the sensitivity of MSE to that of two previously published algorithms by analyzing AF with simulated noise and AF manipulated with vagal stimulation or by adenosine administration to alter the character of the AF. MSE performed favorably in the presence of noise. While all three algorithms distinguished between low and high vagal AF, MSE was the most sensitive in its discrimination. Only MSE could distinguish baseline AF from AF with adenosine. We conclude that our algorithm can distinguish different levels of organization during AF with a greater temporal resolution and sensitivity than previously described algorithms. This algorithm could lead to new ways of analyzing and understanding AF as well as improved techniques in AF therapy.",
keywords = "Adaptive filtering, Atrial fibrillation (AF), Signal processing, Tachyarrhythmia organization",
author = "Sih, {Haris J.} and Zipes, {Douglas P.} and Berbari, {Edward J.} and Olgin, {Jeffrey E.}",
year = "1999",
doi = "10.1109/10.752941",
language = "English",
volume = "46",
pages = "440--450",
journal = "IEEE Transactions on Biomedical Engineering",
issn = "0018-9294",
publisher = "IEEE Computer Society",
number = "4",

}

TY - JOUR

T1 - A high-temporal resolution algorithm for quantifying organization during atrial fibrillation

AU - Sih, Haris J.

AU - Zipes, Douglas P.

AU - Berbari, Edward J.

AU - Olgin, Jeffrey E.

PY - 1999

Y1 - 1999

N2 - Atrial fibrillation (AF) has been described as a 'random' or 'chaotic' rhythm. Evidence suggests that AF may have transient episodes of temporal and spatial organization. We introduce a new algorithm that quantifies AF organization by the mean-squared error (MSE) in the linear prediction between two cardiac electrograms. This algorithm calculates organization at a finer temporal resolution (~300 ms) than previously published algorithms. Using canine atrial epicardial mapping data, we verified that the MSE algorithm showed nonfibrillatory rhythms to be significantly more organized than fibrillatory rhythms (p < .00001). Further, we compared the sensitivity of MSE to that of two previously published algorithms by analyzing AF with simulated noise and AF manipulated with vagal stimulation or by adenosine administration to alter the character of the AF. MSE performed favorably in the presence of noise. While all three algorithms distinguished between low and high vagal AF, MSE was the most sensitive in its discrimination. Only MSE could distinguish baseline AF from AF with adenosine. We conclude that our algorithm can distinguish different levels of organization during AF with a greater temporal resolution and sensitivity than previously described algorithms. This algorithm could lead to new ways of analyzing and understanding AF as well as improved techniques in AF therapy.

AB - Atrial fibrillation (AF) has been described as a 'random' or 'chaotic' rhythm. Evidence suggests that AF may have transient episodes of temporal and spatial organization. We introduce a new algorithm that quantifies AF organization by the mean-squared error (MSE) in the linear prediction between two cardiac electrograms. This algorithm calculates organization at a finer temporal resolution (~300 ms) than previously published algorithms. Using canine atrial epicardial mapping data, we verified that the MSE algorithm showed nonfibrillatory rhythms to be significantly more organized than fibrillatory rhythms (p < .00001). Further, we compared the sensitivity of MSE to that of two previously published algorithms by analyzing AF with simulated noise and AF manipulated with vagal stimulation or by adenosine administration to alter the character of the AF. MSE performed favorably in the presence of noise. While all three algorithms distinguished between low and high vagal AF, MSE was the most sensitive in its discrimination. Only MSE could distinguish baseline AF from AF with adenosine. We conclude that our algorithm can distinguish different levels of organization during AF with a greater temporal resolution and sensitivity than previously described algorithms. This algorithm could lead to new ways of analyzing and understanding AF as well as improved techniques in AF therapy.

KW - Adaptive filtering

KW - Atrial fibrillation (AF)

KW - Signal processing

KW - Tachyarrhythmia organization

UR - http://www.scopus.com/inward/record.url?scp=0032948822&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032948822&partnerID=8YFLogxK

U2 - 10.1109/10.752941

DO - 10.1109/10.752941

M3 - Article

VL - 46

SP - 440

EP - 450

JO - IEEE Transactions on Biomedical Engineering

JF - IEEE Transactions on Biomedical Engineering

SN - 0018-9294

IS - 4

ER -