Window Polarization in PCA-based Analysis of Non-Invasive Fetal ECG recordings

The importance of fetal monitoring through the different stages of pregnancy has recently expanded the interest of the research community in Non-Invasive Fetal Electrocardiography (NI-fECG). This technique makes use of multi-channel, maternal abdominal electrocardiogram (ECG) recordings, acquired from several electrodes placed on the mother's abdomen, to extract information from the fetal ECG component. While wavelets have been shown to be a very useful tool to denoise these signals, clustering and other techniques can be used for the identification of the characteristic segments in the fetal ECG component. However, the selection of the appropriate channels within the abdominal ECG recordings remains a challenge. For this purpose, Principal Component Analysis (PCA) may be used to avoid discarding noisy channels during processing and to optimize the extraction of the fetal ECG, since the abdominal ECG combines the fetal ECG, the maternal ECG and several other artifacts and noises. This research seeks to solve one of the existing challenges when performing a PCA-based analysis of NI-fECG recordings, which is the wrong polarization of the resulting wave. The presented algorithm has been trained with the Physionet "Abdominal and Direct ECG" database. In addition, it has also been possible to solve the problems of wave continuity. Finally, visual inspection of the resulting waves allows to verify that the proposed algorithm meets its basic objectives and is a valid baseline for a PCA-based processing framework of NI-fECG recordings. This will be a useful tool for improving clustering-based analysis of fetal ECG features.