Key result
A physiology-based source separation technique performed slightly better than augmented PCA and ICA, outperformed standard PCA and ICA, and was more robust for fetal QRS detection.
A novel physiology-based source separation technique improves the robustness and signal-to-noise ratio of non-invasive fetal ECG monitoring compared to standard PCA and ICA methods.
May aid non-invasive fetal ECG monitoring; extends source separation methods but remains hypothesis-generating without prospective validation.
The use of the non-invasively obtained fetal electrocardiogram (ECG) in fetal monitoring is complicated by the low signal-to-noise ratio (SNR) of ECG signals. Even after removal of the predominant interference (i.e. the maternal ECG), the SNR is generally too low for medical diagnostics, and hence additional signal processing is still required. To this end, several methods for exploiting the spatial correlation of multi-channel fetal ECG recordings from the maternal abdomen have been proposed in the literature, of which principal component analysis (PCA) and independent component analysis (ICA) are the most prominent. Both PCA and ICA, however, suffer from the drawback that they are blind source separation (BSS) techniques and as such suboptimum in that they do not consider a priori knowledge on the abdominal electrode configuration and fetal heart activity. In this paper we propose a source separation technique that is based on the physiology of the fetal heart and on the knowledge of the electrode configuration. This technique operates by calculating the spatial fetal vectorcardiogram (VCG) and approximating the VCG for several overlayed heartbeats by an ellipse. By subsequently projecting the VCG onto the long axis of this ellipse, a source signal of the fetal ECG can be obtained. To evaluate the developed technique, its performance is compared to that of both PCA and ICA and to that of augmented versions of these techniques (aPCA and aICA; PCA and ICA applied on preprocessed signals) in generating a fetal ECG source signal with enhanced SNR that can be used to detect fetal QRS complexes. The evaluation shows that the developed source separation technique performs slightly better than aPCA and aICA and outperforms PCA and ICA and has the main advantage that, with respect to aPCA/PCA and aICA/ICA, it performs more robustly. This advantage renders it favorable for employment in automated, real-time fetal monitoring applications.
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Vullings et al. (2010) studied Fetal monitoring / low amplitude fetal ECG. Physiology-based source separation technique vs. PCA, ICA, aPCA, and aICA was evaluated on Fetal QRS detection and generation of a fetal ECG source signal with enhanced SNR. A physiology-based source separation technique performed slightly better than augmented PCA and ICA, outperformed standard PCA and ICA, and was more robust for fetal QRS detection.
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