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

Jeon Lee, Mi Hye Song, Dong Gu Shin, Kyoung Joung Lee

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


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 crosscorrelation coefficient (ρ) 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 ρ = 0.938 ± 0.016 and NMSE = 0.243 ± 0.051 for simulated AF ECGs and VR = 1.190 ± 0.476 and S = 0.967 ± 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 singlelead 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.

Original languageEnglish (US)
Pages (from-to)801-811
Number of pages11
JournalMedical and Biological Engineering and Computing
Issue number8
StatePublished - Aug 2012
Externally publishedYes


  • Atrial activity
  • Averaged beat subtraction
  • Electrocardiogram
  • Event synchronous adaptive filter
  • Fibrillatory rate

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computer Science Applications


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