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

Title
Event synchronous adaptive filter based atrial activity estimation in single-lead atrial fibrillation electrocardiograms
Author(s)
신동구송미혜[송미혜]이전[이전]이경정[이경정]
Keywords
BLIND SOURCE SEPARATION; VENTRICULAR ACTIVITY; SURFACE ELECTROCARDIOGRAMS; FREQUENCY-ANALYSIS; ECG; CANCELLATION; WAVE; EXTRACTION; DIAGNOSIS
Issue Date
201208
Publisher
SPRINGER HEIDELBERG
Citation
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, v.50, no.8, pp.801 - 811
Abstract
In this paper, an event synchronous adaptive filter (ESAF) is proposed to estimate atrial activity (AA) from a single-lead AF ECG in real time. The proposed ESAF is a kind of adaptive filter designed to have the reference fed with the impulse train synchronized with the R peak in a raw atrial fibrillation (AF) ECG and to input the timely delayed AF ECG into the primary input. To assess the performance, for ten simulated AF ECGs, the cross-correlation coefficient (rho) and the normalized mean square error (NMSE) between estimated AAs and ten original simulated AAs were calculated and, for ten real AF ECGs, the ventricular residue (VR) in QRS interval and similarity (S) in non-QRS interval were computed. As a result, these four parameters were revealed as rho = 0.938 +/- A 0.016 and NMSE = 0.243 +/- A 0.051 for simulated AF ECGs and VR = 1.190 +/- A 0.476 and S = 0.967 +/- A 0.041 for real AF ECGs. These results were found to be better than those of the averaged beat subtraction (ABS) method, which had been previously considered the only way to estimate AA automatically in real time. In conclusion, even with single-lead AF ECGs, the proposed method estimated AAs accurately and calculated the atrial fibrillatory frequencies, the most valuable index in AF maintenance and therapy evaluation, with a remarkably low computational cost.
URI
http://hdl.handle.net/YU.REPOSITORY/27496http://dx.doi.org/10.1007/s11517-012-0931-7
ISSN
0140-0118
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의과대학 > 내과학교실 > Articles
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