使用EHG源连通性的子宫网络图分析

Saeed Zahran, C. Marque, Mahmoud Hassan, M. Yochum, N. Nader, W. Falou, M. Khalil
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引用次数: 4

摘要

新出现的证据表明,子宫信号的连通性分析是表征妊娠和分娩收缩的有力工具。在这里,我们介绍了从反映子宫肌电活动的宫电图(EHG)信号中识别的子宫源之间的连通性的研究结果。我们首先评估了EHG源连通性处理中涉及的两个关键步骤的影响:i)反问题解决中使用的算法和ii)用于估计功能连通性的方法。我们评估了三种不同的反解(重建子宫源的动力学)和三种连接措施(计算重建源之间的统计耦合)。将逆/连通方法的每种组合得到的网络与模型生成的参考网络(地面真值)进行比较。然后将该方法应用于真实的EHG信号,以区分妊娠和阵痛。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Graph analysis of uterine networks using EHG source connectivity
Emerging evidence show that the connectivity analysis of the uterine signals is a powerful tool in characterizing pregnancy and labor contractions. Here, we present the results of studying the connectivity between uterine sources identified from the electrohysterogram (EHG) signals, which reflects the electrical activity of the uterine muscle. We started by evaluating the effect of the two key steps involved in EHG source connectivity processing: i) the algorithm used in the solution of the inverse problem and ii) the method used for the estimation of the functional connectivity. We evaluate three different inverse solutions (to reconstruct the dynamics of uterine sources) and three connectivity measures (to compute statistical couplings between the reconstructed sources). The networks obtained by each combination of the inverse/connectivity methods were compared to a reference network (ground truth) generated by the model. The method was then applied to real EHG signals in order to discriminate pregnancy and labor contractions.
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