Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Physiol Meas. 2010 Jul;31(7):935-51. doi: 10.1088/0967-3334/31/7/005. Epub 2010 Jun 7.
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.
非侵入式胎儿心电图 (ECG) 在胎儿监测中的应用受到 ECG 信号信噪比 (SNR) 低的限制。即使去除主要干扰（即母体 ECG）后，SNR 通常仍然太低，无法进行医学诊断，因此仍需要额外的信号处理。为此，文献中提出了几种利用来自母体腹部的多通道胎儿 ECG 记录的空间相关性的方法，其中主成分分析 (PCA) 和独立成分分析 (ICA) 最为突出。然而，PCA 和 ICA 都存在一个缺点，即它们是盲源分离 (BSS) 技术，因此不是最优的，因为它们不考虑腹部电极配置和胎儿心脏活动的先验知识。在本文中，我们提出了一种基于胎儿心脏生理学和电极配置知识的源分离技术。该技术通过计算空间胎儿向量心电图 (VCG) 并通过椭圆近似多个重叠心跳的 VCG 来操作。随后将 VCG 投影到该椭圆的长轴上，可以获得胎儿 ECG 的源信号。为了评估所开发的技术，将其性能与 PCA 和 ICA 以及这些技术的增强版本 (aPCA 和 aICA；应用于预处理信号的 PCA 和 ICA) 进行比较，以生成具有增强 SNR 的胎儿 ECG 源信号，该信号可用于检测胎儿 QRS 复合体。评估表明，所开发的源分离技术的性能略优于 aPCA 和 aICA，优于 PCA 和 ICA，并且具有主要优势，即与 aPCA/PCA 和 aICA/ICA 相比，它更稳健。这一优势使其有利于应用于自动化、实时胎儿监测应用。
