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Vectorcardiographic loop alignment for fetal movement detection using the Expectation-Maximization algorithm and Support Vector Machines

机译:矢量卡达图循环对齐用于使用期望最大化算法和支持向量机的胎动检测

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Reduced fetal movement is an important parameter to assess fetal distress. Currently, no suitable methods are available that can objectively assess fetal movement during pregnancy. Fetal vectorcardiographic (VCG) loop alignment could be such a method. In general, the goal of VCG loop alignment is to correct for motion-induced changes in the VCGs of (multiple) consecutive heartbeats. However, the parameters used for loop alignment also provide information to assess fetal movement. Unfortunately, current methods for VCG loop alignment are not robust against low-quality VCG signals. In this paper, a more robust method for VCG loop alignment is developed that includes a priori information on the loop alignment, yielding a maximum a posteriori loop alignment. Classification, based on movement parameters extracted from the alignment, is subsequently performed using support vector machines, resulting in correct classification of (absence of) fetal movement in about 75% of cases. After additional validation and optimization, this method can possibly be employed for continuous fetal movement monitoring.
机译:减少的胎儿运动是评估胎儿窘迫的重要参数。目前,没有合适的方法可以客观地评估怀孕期间的胎儿运动。胎儿矢量卡达(VCG)环路对齐可能是这样的方法。通常,VCG环路对准的目标是校正(多个)连续心跳的VCG中的运动引起的变化。然而,用于环路对准的参数还提供了评估胎儿运动的信息。遗憾的是,VCG环路对准的当前方法对低质量VCG信号不稳定。在本文中,开发了一种更稳健的VCG环路对准方法,其包括关于环路对准的先验信息,产生最大后循环对准。基于从对准提取的运动参数进行分类,随后使用支持载体机进行,导致胎儿运动的胎儿运动的正确分类,在约75%的情况下。在额外的验证和优化之后,该方法可能用于连续胎儿运动监测。

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