The electrical activity of the uterus, i.e. the electrohysterogram (EHG), is one of the most prominent tool for preterm labour. There is no standard acquisition set up and often the EHG is corrupted with different types of noise: maternal and fetal electrocardiogram (mECG, fECG), electrical activity of the skeletal muscles, movement artifacts, power line interference (PLI) etc. Moreover, some of these noises overlap in frequency domain with the EHG. Thus, simple linear filtering approaches are not adequate. In this paper the empirical mode decomposition (EMD), a simple and data driven method, is proposed for EHG denoising. The method is evaluated on simulated data having different signal to noise ratios (SNRs) obtaining promising results.

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The acquisition of the fetal electrocardiogram (fECG) signal via abdominal electrodes placed on the maternal abdomen represents an alternative method to the one used currently in clinical practice. It has the advantage that is noninvasive and can be used for long term monitoring of the fetal wellbeing. However, the limit is the low signal to noise ratio (SNR). The abdominal signal (ADS) recorded with the electrodes contains not only the signal of interest, the fECG signal, but also other disturbing signals with a much higher energy than the fECG signal. One of the most disturbing signals is the power line interference (PLI) signal which has a frequency of 50 Hz and usually contains also its harmonics. In this paper different notch filters are implemented and their performance is evaluated on cancelling the PLI signal from the ADS. Because the morphology of the fECG signal represents an important tool of investigating the fetus health status, the influence of the filters on the shape of the signal is stressed out.

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