January 1, 2001IEEE Transactions on Biomedical Engineering

Atrial activity enhancement by Wiener filtering using an artificial neural network

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Population

ECG signals from the MIT-BIH arrhythmia database

Comparison

Ventricular activity cancellation using an Elman… vs Previously published adaptive cancellation scheme

Authors

CVC. VasquezInstitut polytechnique de Grenoble AHAura Hernández-SabatéUniversitat Autònoma de Barcelona FMF. MoraUniversidad Complutense de Madrid

Discussion

Member takes

Implication

May aid noisy ECG analysis for AF detection; extends adaptive methods but remains hypothesis-generating pending clinical validation.

Structured PICO

Population

ECG signals from the MIT-BIH arrhythmia database

Intervention

Ventricular activity cancellation using an Elman dynamic time delay neural network (TDNN) with nine input samples and 20 neurons

Comparator

Previously published adaptive cancellation scheme

Outcome

Quantitative measures of performance (robustness during noisy episodes and QRS morphology variations)

A novel neural network-based technique for ventricular activity cancellation improves robustness in ECG signal processing for P-wave and atrial fibrillation detection.

Cite This Study

Vasquez et al. (2001) studied this question.

synapsesocial.com/papers/6a7e136a0e93fe1c4a5bf7ab https://doi.org/10.1109/10.936371

Topics

Atrial fibrillation Persistent AF management

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Atrial activity enhancement by Wiener filtering using an artificial neural network

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Topics

Atrial activity enhancement by Wiener filtering using an artificial neural network

Discussion

Member takes

Implication

Structured PICO

Cite This Study

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Topics

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