Literature DB >> 1735788

Diagnosis of atrial fibrillation from surface electrocardiograms based on computer-detected atrial activity.

J Slocum1, A Sahakian, S Swiryn.   

Abstract

A computerized method to detect atrial fibrillatory activity on the surface electrocardiogram is presented. After ventricular activity was canceled by creating a remainder electrocardiogram, significant differences were found in the percent power of the remainder electrocardiograms for a group of rhythms with atrial fibrillation (mean +/- SD; lead V1, 47.4 +/- 29.7%; lead II, 39.4 +/- 26.8%) and a control group (irregular rhythms or rhythms without readily detectable P waves; lead V1, 17.6 +/- 14.6%; lead II, 19.2 +/- 13.9%) for both leads (p less than 0.0001). A discrimination algorithm that classified a rhythm as atrial fibrillation if the percent power was greater than 32% and if noncoupled P waves were not present had a specificity of 90.0% and a sensitivity of 69.7% for the training set and a specificity of 87.8% and a sensitivity of 68.3% for the test set. In addition, the algorithm correctly detected all 66 of the 66 sinus rhythms tested. The algorithm produced good results that may be incorporated into arrhythmia interpretation systems to improve their specificity.

Entities:  

Mesh:

Year:  1992        PMID: 1735788     DOI: 10.1016/0022-0736(92)90123-h

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


  11 in total

1.  Event synchronous adaptive filter based atrial activity estimation in single-lead atrial fibrillation electrocardiograms.

Authors:  Jeon Lee; Mi-hye Song; Dong-gu Shin; Kyoung-joung Lee
Journal:  Med Biol Eng Comput       Date:  2012-06-21       Impact factor: 2.602

2.  Patients with persistent atrial fibrillation taking oral verapamil exhibit a lower atrial frequency on the ECG.

Authors:  Andreas Bollmann; Kai Sonne; Hans-Dieter Esperer; Ines Toepffer; Helmut U Klein
Journal:  Ann Noninvasive Electrocardiol       Date:  2002-04       Impact factor: 1.468

3.  Analysis of atrial fibrillatory activity from high-resolution surface electrocardiograms: Evaluation and application of a new system.

Authors:  Herko Grubitzsch; Diethelm Modersohn; Thomas Leuthold; Wolfgang Konertz
Journal:  Exp Clin Cardiol       Date:  2008

4.  Time and frequency series combination for non-invasive regularity analysis of atrial fibrillation.

Authors:  Carlos Vayá; José Joaquín Rieta
Journal:  Med Biol Eng Comput       Date:  2009-05-26       Impact factor: 2.602

5.  Estimation of atrial fibrillatory wave from single-lead atrial fibrillation electrocardiograms using principal component analysis concepts.

Authors:  F Castells; C Mora; J J Rieta; D Moratal-Pérez; J Millet
Journal:  Med Biol Eng Comput       Date:  2005-09       Impact factor: 3.079

6.  Frequency analysis of atrial fibrillation from the surface electrocardiogram.

Authors:  Daniela Husser; Martin Stridh; Leif Sornmo; S Bertil Olsson; Andreas Bollmann
Journal:  Indian Pacing Electrophysiol J       Date:  2004-07-01

7.  Automatic Detection of Atrial Fibrillation Based on Continuous Wavelet Transform and 2D Convolutional Neural Networks.

Authors:  Runnan He; Kuanquan Wang; Na Zhao; Yang Liu; Yongfeng Yuan; Qince Li; Henggui Zhang
Journal:  Front Physiol       Date:  2018-08-30       Impact factor: 4.566

Review 8.  Photoplethysmography based atrial fibrillation detection: a review.

Authors:  Tania Pereira; Nate Tran; Kais Gadhoumi; Michele M Pelter; Duc H Do; Randall J Lee; Rene Colorado; Karl Meisel; Xiao Hu
Journal:  NPJ Digit Med       Date:  2020-01-10

9.  Atrial Fibrillation Detection During Sepsis: Study on MIMIC III ICU Data.

Authors:  Syed Khairul Bashar; Md Billal Hossain; Eric Ding; Allan J Walkey; David D McManus; Ki H Chon
Journal:  IEEE J Biomed Health Inform       Date:  2020-11-06       Impact factor: 7.021

10.  Automatic online detection of atrial fibrillation based on symbolic dynamics and Shannon entropy.

Authors:  Xiaolin Zhou; Hongxia Ding; Benjamin Ung; Emma Pickwell-MacPherson; Yuanting Zhang
Journal:  Biomed Eng Online       Date:  2014-02-17       Impact factor: 2.819

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