Non parametric modelling of ECG: Applications to denoising and single sensor fetal ECG extraction

Bertrand Rivet 1 Mohammad Niknazar 1 Christian Jutten 1
1 GIPSA-VIBS - VIBS
GIPSA-DIS - Département Images et Signal
Abstract : In this work, we tackle the problem of fetal electrocardio- gram (ECG) extraction from a single sensor. The proposed method is based on non-parametric modelling of the ECG signal described thanks to its second order statistics. Each assumed source in the mixture is thus modelled as a second order process thanks to its covariance function. This modelling allows to reconstruct each source by maximizing the re- lated posterior distribution. The proposed method is tested on synthetic data to evaluate its performance behavior to denoise ECG. It is then ap- plied on real data to extract fetal ECG from a single maternal abdominal sensor.
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Bertrand Rivet, Mohammad Niknazar, Christian Jutten. Non parametric modelling of ECG: Applications to denoising and single sensor fetal ECG extraction. 10th International Conference on Latent Variable Analysis and Source Separation (LVA/ICA 2012), Mar 2012, Tel-Aviv, Israel. pp.470-477. ⟨hal-00681534⟩

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