Atrial activity estimation using periodic component analysis
| Autor: | Andres Camacho, Jorge Igual, Julio Miró-Borrás, Raul Llinares |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
medicine.diagnostic_test
Covariance matrix business.industry Speech recognition Bandwidth (signal processing) Atrial fibrillation Pattern recognition medicine.disease Blind signal separation Component analysis Discriminative model cardiovascular system medicine Algorithm design cardiovascular diseases Artificial intelligence business Electrocardiography Mathematics |
| Zdroj: | IJCNN |
| DOI: | 10.1109/ijcnn.2010.5596951 |
| Popis: | The interest in the study and analysis of Atrial Fibrillation (AF) has increased significantly in the last decades. A correct estimation of the atrial activity is a crucial previous step for AF analysis. Different methods based on Blind Source Separation of 12-lead electrocardiogram (ECG) have been proposed. However, these techniques are based only on the statistical independence of the sources, and usually require a postprocessing step to identify the signal of interest. We present a method that also uses a multilead approach in order to use all the information available in the leads, but it focuses on the discriminative properties of the spectrum of the atrial signal with respect to the non-atrial components. The atrial rhythm can be considered as a pseudo-periodic signal with a main atrial frequency in the range 3–10 Hz. The bandwidth and shape of the spectrum is related to the patient and the kind of tachyrhythmia. Another advantage is that the way the atrial component is extracted is based on algebraic methods, avoiding the adjustment of learning rates and other parameters. The method is applied successfully to real data. |
| Databáze: | OpenAIRE |
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