Fetal ECG Signal Processing for Fetal Monitoring Based on BSS and EMD

Cardiac abnormalities are, currently, among the most widespread causes of intrauterine deaths resulting from congenital malformations. An early diagnosis could contribute to reducing their number. Isolation of the fetal electrocardiogram (fECG) from abdominal signals is one of the most promising approaches due to its advantages compared to other fetal monitoring methods. However, the multiple sources of interference that alter abdominal signals make them difficult to process and interpret. Thus, in the present work, an algorithm is proposed to isolate the fECG from such signals and to extract the fetal heart rate (fHR). It is divided in 3 main stages: (1) Preprocessing, in which both Empirical Mode Decomposition (EMD) and Empirical Wavelet Transform (EWT) are used to eliminate motion artifacts (MA), baseline wander (BA) and powerline interference (PLI), (2) Maternal electrocardiogram (mECG) approximation and removal, using the Fractional Fourier Transform (FrFT) and Maximum Likelihood Estimation (MLE) and (3) fECG approximation using Independent Component Analysis (ICA) and a bandpass filter to facilitate the detection of the fetal R peaks and to obtain an approximation of fHR. The algorithm was tested on the Abdominal and Direct Fetal ECG Database (adfecgdb) available on the Physionet platform.