Automatic detection of atrial fibrillation and flutter by wave rectification method

Rapid detection of atrial flutter or fibrillation is needed in intensive care or home ECG monitoring with alarm generation, and in portable monitors with warning function, etc. Detection and assessment of these atrial abnormalities is necessary in computerized morphological analysis as well, to deci...

Full description

Saved in:
Bibliographic Details
Published in:Journal of medical engineering & technology 2001, Vol.25 (5), p.217-221
Main Author: Christov, G. Bortolan, I. Daskalov, I.
Format: Article
Language:English
Subjects:
Atrial Fibrillation - diagnosis
Atrial Flutter - diagnosis
Biological and medical sciences
Electrocardiography
Electrocardiography. Vectocardiography
Electrodiagnosis. Electric activity recording
Humans
Investigative techniques, diagnostic techniques (general aspects)
Medical sciences
Sensitivity and Specificity
Signal Processing, Computer-Assisted
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Rapid detection of atrial flutter or fibrillation is needed in intensive care or home ECG monitoring with alarm generation, and in portable monitors with warning function, etc. Detection and assessment of these atrial abnormalities is necessary in computerized morphological analysis as well, to decide whether parameter measurements should be rejected, restricted to QRS and/or T wave only, or limited to those leads where atrial flutter or fibrillation waves are less expressed. A method for the detection and measurement of atrial flutter and fibrillation in the T-P segments of the ECG is proposed. An atrial flutter/ fibrillation parameter (AFF) is defined as the mean value of the differentiated filtered and rectified signal in these segments. The AFF has been measured in 329 patients from an annotated atrial flutter-fibrillation database. A threshold of AFF=0.35% with respect to the maximum signal excursion was chosen by a heuristic algorithm, to separate patients with atrial arrhythmia. The accuracy of the method was 91.8%. The positive and negative detection errors of the AFF classification are discussed.
ISSN:0309-1902
1464-522X
DOI:10.1080/03091900110065942