학술논문

A node-wise analysis of the uterine muscle networks for pregnancy monitoring
Document Type
Conference
Source
2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual International Conference of the. :712-715 Aug, 2016
Subject
Bioengineering
Pregnancy
Electrodes
Monitoring
Correlation
Coherence
Graph theory
Muscles
Language
ISSN
1557-170X
1558-4615
Abstract
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 (4×4 matrix) EHG signals recorded from the women's 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.