模拟子宫收缩:图论和基于连接的EHG信号分析

Kamil Bader Eldine , Noujoud Nader , Mohamad Khalil , Catherine Marque
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引用次数: 0

摘要

早产是死亡率和发病率的主要原因,因此需要改进早产预测和管理。解决这一挑战的一个有希望的方法是分析子宫电图(EHG)信号,它记录了调节子宫收缩的电活动。分析脑电图信号的特征为检测胎儿提供了有价值的数据。在本文中,我们提出了一个新的框架,使用模拟EHG信号来识别子宫连通性敏感的特征。我们关注的是分娩过程中EHG信号的传播,由多个电极记录。我们模拟了不同组的EHG信号,以确定哪种连接方法和图形参数最能代表驱动子宫同步的两个主要因素:短距离传播(通过电扩散,ED)和远距离同步(通过机械传导,EDM)。在子宫模型中,首先通过改变组织阻力,仅通过电扩散模拟信号;其次,通过保持组织阻力恒定和改变影响机械传导的模型参数,利用ED和机械传导模拟信号。我们使用双极技术通过模拟放置在孕妇腹部的16个表面电极组成的4 × 4矩阵来构建我们的模拟EHGs。我们的研究结果表明,即使是简化的机电模型也可以利用模拟的EHG信号来监测子宫同步。Fscore对真实和模拟EHG信号的选择之间的差异表明,当使用平均函数时,最佳特征是H2(Str), FW_h2单独以及与PR, BC和CC联合使用。在机械转导过程中,最佳特征是H2单独或与Str, R2(PR)和ICOH(Str)联合使用。表明电扩散变化的最佳特征是H2单独和与Eff, PR和BC结合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulated uterine contractions: Graph theory and connectivity-based analysis of EHG signals
Preterm labor represents the prominent cause of mortality and morbidity, highlighting the important need for improved preterm contraction prediction and management. One promising approach to resolving this challenge is to analyze the electrohysterographic (EHG) signal, which records the electrical activity regulating uterine contractions. Analyzing the features of the EHG signal contributes valuable data to detect labor. In this paper, we propose a new framework using simulated EHG signals to identify features sensitive to uterine connectivity. We focus on EHG signal propagation during labor, recorded by multiple electrodes. We simulated EHG signals in different groups to determine which connectivity methods and graph parameters best represent the two main factors driving uterine synchronization: short-distance propagation (via electrical diffusion, ED) and long-distance synchronization (via mechanotransduction, EDM). Using the uterine model, signals were first simulated using just electrical diffusion by modifying the tissue resistance; second, signals were simulated using ED and mechanotransduction by holding the tissue resistance constant and varying the model parameters that affect mechanotransduction. We used the bipolar technique to construct our simulated EHGs by modeling a matrix of 16 surface electrodes organized in a 4 × 4 matrix placed on the pregnant woman’s abdomen. Our results show that even a simplified electromechanical model can be useful for monitoring uterine synchronization using simulated EHG signals. The differences seen between the selection performed by Fscore on real and simulated EHG signals show that when employing the mean function, the best features are H2(Str), FW_h2 alone, and in combination with PR, BC, and CC. The best characteristics that demonstrate a shift in the mechanotransduction process are H2 alone or in combination with Str, R2(PR), and ICOH(Str). The best characteristics that demonstrate a shift in electrical diffusion are H2 alone and in combination with Eff, PR, and BC.
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来源期刊
Biomedical engineering advances
Biomedical engineering advances Bioengineering, Biomedical Engineering
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