Paper Info
Title
Connectivity Measures of Uterine Activity using Magnetomyography.
Abstract
This work explores the use of graph-theoretical metrics of network topography to investigate interactions in the uterine activity using a multi-channel SQUID array. Magnetomyography (MMG) is a noninvasive technique that records magnetic fields associated with the uterine activity. Graph analysis was applied to 30s no-overlap epochs of MMG data for evaluating the evolution of local and global connectivity, and centrality indicators within the network. Binary graphs were obtained by applying a range of thresholds from 10% to 35% of the strongest edges preserved. Network analysis was applied to 24 simulated MMG data when independent noise realizations were added. Simulated data was generated from a multiscale forward model that uses a realistic uterus representation. Additionally, we applied network analysis to repeated real MMG measurements obtained from a subject at different gestational ages (GA) to observe the evolution of the network until subject reaches active labor. Results show in the simulation setting that network metrics were higher during the burst activity reflecting the propagation activity of the signal across the uterus of the multiscale mathematical model. The local efficiency values were higher than the global efficiency for any threshold used. For real MMG recordings, global and local efficiency, and clustering coefficient values increased as the patient approached active labor at any binarized threshold whereas betweenness centrality quantity decreased with days to active labor.
Year
DOI
Venue
2018
10.1109/EMBC.2018.8513498
EMBC
Field
DocType
Volume
Computer vision,Pattern recognition,Computer science,Centrality,Network topology,Power graph analysis,Betweenness centrality,Artificial intelligence,Network analysis,Clustering coefficient,Metrics,Binary number
Conference
2018
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Diana I. Escalona-Vargas1123.27
M. Zhang201.69
Arye Nehorai31257126.92
Hari Eswaran4369.23