An Online Subspace Denoising Algorithm for Maternal ECG Removal from Fetal ECG Signals

Marzieh Fatemi (1) , Reza Sameni (1)

1 School of Electrical & Computer Engineering

Noninvasive extraction of the fetal electrocardiogram (fECG) from multichannel maternal abdomen recordings is an emerging technology used for fetal cardiac monitoring and diagnosis. The strongest interference for the fECG is the maternal ECG (mECG), which is not always removed through conventional methods including blind source separation (BSS), especially for low-rank abdominal recordings. In this work, we address the problem of maternal cardiac signal removal and introduce an online subspace denoising procedure customized for mECG cancellation. The proposed method is a general online denoising framework, which can be used for the extraction of a signal subspace from noisy multichannel observations in low signal-to-noise ratios, using suitable prior information of the signal and/or noise. The method is fairly generic and may also be useful for the separation of other signals and noises. The performance of the proposed technique is evaluated on both real and synthetic data and benchmarked versus state-of-the-art methods.

Mots clés: noninvasive fetal ECG extraction; online generalized eigenvalue decomposition; Online subspace denoising; semi-blind source separation; maternal ECG cancellation

Domaines: Traitement du signal et de l'image [eess.SP]

Marzieh Fatemi, Reza Sameni. An Online Subspace Denoising Algorithm for Maternal ECG Removal from Fetal ECG Signals. 2015. ⟨hal-01389807v2⟩