Spatiotemporal QRST cancellation techniques for analysis of atrial fibrillation

Stridh, Martin; Sörnmo, Leif

doi:10.1109/10.900266

Cited by 283 publications

(219 citation statements)

References 13 publications

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“…The atrial signal was obtained by removing the QRST signal, using spatiotemporal QRST cancellation. 8 The frequency with the highest peak in the frequency spectrum, which is equivalent to AFR, was then determined using Hidden Markov Model (HMM)-based frequency tracking. 9 To reduce residual noise in the atrial activity, the main atrial wave, which constitutes the fundamental waveform of the atrial activity, was obtained from the atrial activity by applying a selective bandpass filter, based on the AFR.…”

Section: Data Collectionmentioning

confidence: 99%

Noninvasive estimation of organization in atrial fibrillation as a predictor of sinus rhythm maintenance

Petersson

Sandberg

Platonov

et al. 2011

Journal of Electrocardiology

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Previous studies indicate that the predictive value of atrial fibrillatory rate in patients undergoing cardioversion of atrial fibrillation (AF) of long duration is limited. The present study investigates signal entropy in this setting. Standard 12-lead electrocardiograms (ECGs) were recorded from 66 consecutive patients with AF undergoing cardioversion and sample entropy estimated. Patients were followed for 4 weeks. At follow-up, 59% of the patients had relapsed to AF. The AF signal entropy of these patients before cardioversion was 0.099 ± 0.015, whereas it was 0.093 ± 0.012 among the 41% maintaining sinus rhythm (P = .02). As hypothesized, signal entropy was lower in patients who maintained sinus rhythm 4 weeks after cardioversion than in those who did not. However, the overlap was large, making its clinical value limited.

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Section: Data Collectionmentioning

confidence: 99%

Noninvasive estimation of organization in atrial fibrillation as a predictor of sinus rhythm maintenance

Petersson

Sandberg

Platonov

et al. 2011

Journal of Electrocardiology

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“…Another cancellation technique like the one described by Stridh 28 cannot be used because it needs three leads.…”

Section: Qt Pattern Cancellationmentioning

confidence: 99%

P and R Wave Detection in Complete Congenital Atrioventricular Block

et al. 2008

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Complete atrioventricular block (type III AVB) is characterized by an absence of P wave transmission to ventricles. This implies that QRS complexes are generated in an autonomous way and are not coordinated with P waves. This work introduces a new algorithm for the detection of P waves for this type of pathology using non-invasive electrocardiographic surface leads.The proposed algorithm is divided into three stages. In the first stage, the R waves located by a QRS detector are used to generate the RR series and time references for the other stages of the algorithm. In the second stage, the ventricular activity (QT segment) is removed by using an adaptive filter that obtains an averaged pattern of the QT segment. In the third stage, a new P wave detector is applied to the residual signal obtained after QT cancellation in order to detect P wave locations and get the PP time series.Eight Holter records from patients with congenital type III AVB were used to verify the proposed algorithm. Although further improvements should be made to improve the algorithm's performance, the results obtained show high average values of sensitivity (90.52 %) and positive prediction (90.98%). KeywordsComplete congenital atrioventricular block, P and R wave detection, QRS, adaptive impulse correlated filter, SNEO.2 2

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“…As input, the method always uses the complex atrial activity signal x, obtained by applying spatiotemporal QRST cancellation [5], followed by the Hilbert transform, to ECG signals.…”

Section: Methodsmentioning

confidence: 99%

“…To evaluate the relationship between S and SNR, this study uses an extended version of the sawtooth model for simulating f-waves proposed in [5], which includes a stochastic component so that more complex f-wave patterns can be generated [11]. The simulated f-waves are composed of two components with equal RMS,…”

Section: Datasets and Performance Evaluationmentioning

confidence: 99%

Signal Quality Assessment of F-waves in Atrial Fibrillation

Henriksson

Petrėnas

Marozas

et al. 2017

Computing in Cardiology Conference (CinC)

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Ambulatory ECG recordings are frequently corrupted by artifacts caused by, e.g., muscle activity or moving electrodes, which complicates the analysis of f-waves and motivates signal quality assessment to improve the reliability of f-wave analysis. Although many methods have been developed for assessing the quality of ECG signals in general, no method deals specifically with f-waves. This study proposes a novel signal quality index (SQI), using a modelbased approach for assessment of f-wave signal quality. To evaluate the performance of the SQI, 189 5-s recordings of f-waves from AF patients are studied, as is the same number of recordings with motion artifacts and electrode movements taken from the MIT-BIH Noise Stress Test Database. The signal quality index is capable of discriminating between f-waves and noisy recordings with an accuracy of 98%. The results suggest that the proposed signal quality index correctly identifies noisy recordings, and can be used to improve the reliability of f-wave analysis.

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Spatiotemporal QRST cancellation techniques for analysis of atrial fibrillation

Cited by 283 publications

References 13 publications

Noninvasive estimation of organization in atrial fibrillation as a predictor of sinus rhythm maintenance

Noninvasive estimation of organization in atrial fibrillation as a predictor of sinus rhythm maintenance

P and R Wave Detection in Complete Congenital Atrioventricular Block

Signal Quality Assessment of F-waves in Atrial Fibrillation

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