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- W4240932505 abstract "Contemporary methods of atrial flutter (AFL), atrial tachycardia (AT), and atrial fibrillation (AF) monitoring, although superior to the standard 12-lead ECG and symptom-based monitoring, are unable to accurately discriminate between AF, AFL and AT. Thus, there is a need to develop accurate, automated, and comprehensive atrial arrhythmia detection algorithms using standard ECG recorders. To this end, we have developed a sensitive and real-time realizable algorithm for accurate AFL and AT detection using any standard electrocardiographic recording. Our novel method for automatic detection of atrial flutter and atrial tachycardia uses a Bayesian approach followed by a high resolution time–frequency spectrum. We find the TQ interval of the electrocardiogram (ECG) corresponding to atrial activity by using a particle filter (PF), and analyze the atrial activity with a high resolution time–frequency spectral method: variable frequency complex demodulation (VFCDM). The rationale for using a high-resolution time–frequency algorithm is that our approach tracks the time-varying fundamental frequency of atrial activity, where AT is within 2.0–4.0 Hz, AFL is within 4.0–5.3 Hz and NSR is found at frequencies less than 2.0 Hz. For classifications of AFL (n = 22), AT (n = 10) and normal sinus rhythms (NSR) (n = 29), we found that our approach resulted in accuracies of 0.89, 0.87 and 0.91, respectively; the overall accuracy was 0.88." @default.
- W4240932505 created "2022-05-12" @default.
- W4240932505 date "2005-03-01" @default.
- W4240932505 modified "2023-10-14" @default.
- W4240932505 title "Author bios" @default.
- W4240932505 doi "https://doi.org/10.1016/s0146-2806(05)00021-6" @default.
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