The abdominal fetal electrocardiogram (fECG), recorded noninvasively via surface electrodes placed on the maternal abdomen, has recently gained significant research attention from physicians due to its advantages over fetal monitoring techniques currently used in clinical practice. However, the fECG signal is often corrupted by different types of noise, generated by biological sources: maternal electrocardiogram (mECG), abdominal skeletal electromyogram (EMG), electrohysterogram (EHG) or non-biological sources: movement artefacts, electromagnetic and electronic noise. The presence of so many types of noise makes the direct fECG analysis impossible and, in addition, the spectrum of the noise is overlapping with the one of the signal of interest, making simple filtering techniques ineffective. In this paper, we propose a new method for abdominal fECG denoising based on a blind source separation method, i.e the independent component analysis (ICA), and empirical mode decomposition (EMD). The performance of the proposed algorithm, called ICA_EMD, was evaluated on both simulated and real data and compared with the performance obtained by ICA, showing a better removal of artefacts without disturbing the fECG signal.

Keywords: Fetal electrocardiogram, Empirical mode decomposition (EMD), Independent component analysis