Atrial fibrillation frequency tracking in ambulatory ECG signals: The significance of signal quality assessment

Paliakaitė‬‬‬, Birutė; Petrėnas, Andrius; Henriksson, Mikael; Skibarkienė, Jurgita; Kubilius, Raimondas; Sörnmo, Leif; Marozas, Vaidotas

doi:10.1016/j.compbiomed.2018.08.027

Cited by 6 publications

(1 citation statement)

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“…(ii) Atrial fibrillation rate was measured with the dominant atrial frequency (DAF), which is estimated from the power spectrum of the extracted f-wave and is considered as one of the most informative f-wave characteristics in the frequency domain (Paliakaitė et al 2018). The DAF was estimated using Welch's method to determine the power spectrum of the extracted f-wave.…”

Section: Evaluation Of the Robustness Of F-wave Features Extractionmentioning

confidence: 99%

A comparative study of the performance of methods for f-wave extraction

et al. 2022

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Objective: This study proposes a novel technique for atrial fibrillatory waves (f-waves) extraction and investigates the performance of the proposed method comparing with different f-wave extraction methods. Approach: We propose a novel technique combining a periodic component analysis (PiCA) and echo state network (ESN) for f-waves extraction, denoted PiCA-ESN. PiCA-ESN benefits from the advantages of using both source separation and nonlinear adaptive filtering. PiCA-ESN is evaluated by comparing with other state-of-the-art approaches, which include template subtraction technique based on principal component analysis, spatiotemporal cancellation, nonlinear adaptive filtering using an echo state neural network, and a source separation technique based on PiCA. Quality assessment is performed on a recently published reference database including a large number of simulated ECG signals in atrial fibrillation (AF). The performance of the f-wave extraction methods is evaluated in terms of signal quality metrics (SNR, ΔSNR) and robustness of f-wave features. Main results: The proposed method offers the best signal quality performance, with a ΔSNR of approximately 22 dB across all 8 sets of the reference database, as well as the most robust extraction of f-wave features, with 75% of all estimates of dominant atrial frequency well below 1 Hz.

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Section: Evaluation Of the Robustness Of F-wave Features Extractionmentioning

confidence: 99%