Frequency analysis of atrial fibrillation

Langley, Philip; Bourke, John; Murray, Alan

doi:10.1109/cic.2000.898456

Cited by 66 publications

(53 citation statements)

References 4 publications

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“…To achieve the source separation, a linear transformation is sought such that the components of the output signal vector become statistically independent, thus representing an estimate of the sources except for (perhaps) scaling and permutation, which are considered as admissible indeterminacies [22]. Some authors have proposed the use of PCA to solve the mixing model between atrial and ventricular activity in AF [23]. However, it is important to remark that the success of PCA relies heavily on the orthogonality of the sources.…”

Section: Signal Separation Methodsmentioning

confidence: 99%

Applications of Signal Analysis to Atrial Fibrillation

Rieta¹,

Alcaraz²

2013

Atrial Fibrillation - Mechanisms and Treatment

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Section: Signal Separation Methodsmentioning

confidence: 99%

Applications of Signal Analysis to Atrial Fibrillation

Rieta¹,

Alcaraz²

2013

Atrial Fibrillation - Mechanisms and Treatment

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“…The prevalence of AF is less than 1% among population under 60 years old, but it increases significantly among those over 70, approximating to 10% in those older than 80 [1]. Recently, spectral analysis has been revealed as a useful tool for atrial fibrillation (AF) description [2]. Furthermore, time-domain methods have been successfully applied in the characterization of AF episodes using the surface electrocardiogram (ECG) [3,4].…”

Section: Introductionmentioning

confidence: 99%

ECG signal quantization effects in the analysis of atrial fibrillation

Vaya

Rieta

2007

2007 Computers in Cardiology

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“…In our case, the main atrial rhythms correspond to 3.88 and 7.07 Hz for the flutter and fibrillation cases, respectively; in addition, we can observe in the figure the harmonics for the flutter case. This atrial frequency band presents slight variations depending on the authors, for example, 4-9 Hz [12,13], 5-10 Hz [14], 3.5-9 Hz [11] or 3-12 Hz [15].…”

Section: On the Periodicity Of The Atrial Activitymentioning

confidence: 99%

Exploiting periodicity to extract the atrial activity in atrial arrhythmias

Llinares

Igual

2011

EURASIP J. Adv. Signal Process.

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Atrial fibrillation disorders are one of the main arrhythmias of the elderly. The atrial and ventricular activities are decoupled during an atrial fibrillation episode, and very rapid and irregular waves replace the usual atrial P-wave in a normal sinus rhythm electrocardiogram (ECG). The estimation of these wavelets is a must for clinical analysis. We propose a new approach to this problem focused on the quasiperiodicity of these wavelets. Atrial activity is characterized by a main atrial rhythm in the interval 3-12 Hz. It enables us to establish the problem as the separation of the original sources from the instantaneous linear combination of them recorded in the ECG or the extraction of only the atrial component exploiting the quasiperiodic feature of the atrial signal. This methodology implies the previous estimation of such main atrial period. We present two algorithms that separate and extract the atrial rhythm starting from a prior estimation of the main atrial frequency. The first one is an algebraic method based on the maximization of a cost function that measures the periodicity. The other one is an adaptive algorithm that exploits the decorrelation of the atrial and other signals diagonalizing the correlation matrices at multiple lags of the period of atrial activity. The algorithms are applied successfully to synthetic and real data. In simulated ECGs, the average correlation index obtained was 0.811 and 0.847, respectively. In real ECGs, the accuracy of the results was validated using spectral and temporal parameters. The average peak frequency and spectral concentration obtained were 5.550 and 5.554 Hz and 56.3 and 54.4%, respectively, and the kurtosis was 0.266 and 0.695. For validation purposes, we compared the proposed algorithms with established methods, obtaining better results for simulated and real registers.

show abstract

Frequency analysis of atrial fibrillation

Cited by 66 publications

References 4 publications

Applications of Signal Analysis to Atrial Fibrillation

Applications of Signal Analysis to Atrial Fibrillation

ECG signal quantization effects in the analysis of atrial fibrillation

Exploiting periodicity to extract the atrial activity in atrial arrhythmias

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