Applications of Nonlinear Methods to Atrial Fibrillation

Alcaraz, Raúl; Rieta, J.J.

doi:10.1007/978-3-319-58709-7_15

Cited by 2 publications

(2 citation statements)

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“…For example, the f -wave repetition rate, i.e., the dominant atrial frequency (DAF), has proven useful for monitoring drug therapy and predicting spontaneous and drug-induced AF termination (Platonov, Corino, Seifert, Holmqvist & Sörnmo 2014). More advanced approaches to characterizing f -wave morphology, e.g., based on nonlinear analysis and entropy measures (Alcaraz & Rieta 2017), can help select patients who would respond to therapies such as electrical cardioversion, catheter ablation, and Maze surgery. In addition, f -wave representation by image mapping techniques has proven useful for noninvasive localization of focal impulse sources of AF (Cuculich, Wang, Lindsay, Faddis, Schuessler, Damiano, Li & Rudy 2010).…”

Section: Introductionmentioning

confidence: 99%

“…More advanced approaches to characterizing f -wave morphology, e.g. those based on nonlinear analysis and entropy measures (Alcaraz and Rieta 2017), can help select patients who would respond to therapies such as electrical cardioversion, catheter ablation, and Maze surgery. In addition, f -wave representation by image mapping techniques has proven useful for noninvasive localization of focal impulse sources of AF (Cuculich et al 2010).…”

Section: Introductionmentioning

confidence: 99%

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Reference database and performance evaluation of methods for extraction of atrial fibrillatory waves in the ECG

2019

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Objective: This study proposes a reference database, composed of a large number of simulated ECG signals in atrial fibrillation (AF), for investigating the performance of methods for extraction of atrial fibrillatory waves (f-waves). Approach: The simulated signals are produced using a recently published and validated model of 12-lead ECGs in AF. The database is composed of eight signal sets which together account for a wide range of characteristics known to represent major challenges in f-wave extraction, including high heart rates, high morphological QRST variability, and the presence of ventricular premature beats. Each set contains 30 5-min signals with different f-wave amplitudes. The database is used for the purpose of investigating the statistical association between different indices, designed either for use with real or simulated signals. Main results: Using the database, which is made available at the Physionet repository of physiological signals, the performance indices unnormalized ventricular residue (uVR), designed for real signals, and the root mean square error, designed for simulated signals, were found to exhibit the strongest association, leading to the recommendation that uVR should be used when characterizing performance in real signals. Significance: The proposed database facilitates the comparison of performance of different f-wave extraction methods and makes it possible to express performance in terms of the error between simulated and extracted f-wave signals.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%