| Paper: | BIO-P1.7 | ||
| Session: | Biomedical Signal Processing I | ||
| Time: | Tuesday, May 16, 10:30 - 12:30 | ||
| Presentation: | Poster | ||
| Topic: | Bio Imaging and Signal Processing: Biomedical signal processing | ||
| Title: | Ventricular and Atrial Activity Estimation Through Sparse ECG Signal Decompositions | ||
| Authors: | Oscar Divorra Escoda, Lorenzo Granai, Mathieu Lemay, Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland; Javier Molinero Hernandez, EPFL / UPC, Switzerland; Pierre Vandergheynst, Jean-Marc Vesin, Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland | ||
| Abstract: | This paper explores a novel approach for ventricular and atrial activities estimation in electrocardiogram (ECG) signals, based on sparse source separation. Sparse decompositions of ECG over signal-adapted multi-component dictionaries can lead to natural separation of its components. In this work, dictionaries of functions adapted to ventricular and atrial activities are respectively defined. Then, the weighted orthogonal matching pursuit algorithm is used to unmix the two components of ECG signals. Despite the simplicity of the approach, results are very promising, showing the capacity of the algorithm to generate realistic estimations of atrial and ventricular activities. | ||
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