The recent past years have seen a noticeable increase of interest in the
correlation analysis of electrohysterographic (EHG) signals in the perspective
of improving the pregnancy monitoring. Here we propose a new approach based on
the functional connectivity between multichannel (4x4 matrix) EHG signals
recorded from the women abdomen. The proposed pipeline includes i) the
computation of the statistical couplings between the multichannel EHG signals,
ii) the characterization of the connectivity matrices, computed by using the
imaginary part of the coherence, based on the graph-theory analysis and iii)
the use of these measures for pregnancy monitoring. The method was evaluated on
a dataset of EHGs, in order to track the correlation between EHGs collected by
each electrode of the matrix (called node-wise analysis) and follow their
evolution along weeks before labor. Results showed that the strength of each
node significantly increases from pregnancy to labor. Electrodes located on the
median vertical axis of the uterus seemed to be the more discriminant. We
speculate that the network-based analysis can be a very promising tool to
improve pregnancy monitoring.Comment: 4 pages, 3 figures, accepted in the IEEE EMBC conferanc
