Issues and research on foetal electrocardiogram signal elicitation

The existence of Electrocardiography (ECG) came to light over a century ago, yet the acquisition and elicitation of non-invasive foetal electrocardiogram (fECG) is still in infancy despite mammoth advances in clinical electrocardiography, advanced Biomedical signal processing techniques and fast growing engineering technology. The acquisition of foetal ECG becomes a challenging task since it is perilous for a direct contact over the foetus. Moreover, the non-invasive abdominal ECG (aECG) measurements obtained over the surface of a maternal abdomen contains several bioelectric potentials like maternal heart activity, foetal heart activity, maternal muscle activity, foetal movement activity, generated potentials by respiration and stomach activity, and noise (thermal noise, noise generated from electrode-skin contact). The strong Maternal Electrocardiogram (mECG) along with the weak fECG in the recordings obtained from a mother is overlapping in time as well as in frequency. Hence separation of these signals cannot be accomplished by simple windowing or filtering. Over the years numerous researchers have put enormous efforts in signal processing and biomedical engineering for humanizing the foetal ECG acquisition techniques used by the physiologists. The fECG signal is a vital information source to assist physicians for precise timely decisions during labor. Some of the recently developed algorithms by researchers have given remarkable results for fECG acquisition. The focus of this paper is to review these existing algorithms for non-invasive detection and elicitation of fECG in terms of their performance and capabilities with respect to standard databases available worldwide.