Dictionary learning for the sparse modelling of atrial fibrillation in ECG signals

@article{Mailh2009DictionaryLF,
  title={Dictionary learning for the sparse modelling of atrial fibrillation in ECG signals},
  author={Boris Mailh{\'e} and R{\'e}mi Gribonval and Fr{\'e}d{\'e}ric Bimbot and Mathieu Lemay and Pierre Vandergheynst and Jean-Marc Vesin},
  journal={2009 IEEE International Conference on Acoustics, Speech and Signal Processing},
  year={2009},
  pages={465-468}
}
We propose a new method for ventricular cancellation and atrial modelling in the ECG of patients suffering from atrial fibrillation. Our method is based on dictionary learning. It extends both the average beat subtraction and the sparse source separation approaches. Experiments on synthetic data show that this method can almost completely suppress the ventricular activity, but it generates some artifacts. Contrary to other ventricular cancellations methods, our approach also learns a model for… CONTINUE READING
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