Łukasiewicz Research Network-Institute of Medical Technology and Equipment, PL41800 Zabrze, Poland.
Department of Cybernetics, Nanotechnology and Data Processing, Silesian University of Technology, PL44100 Gliwice, Poland.
Sensors (Basel). 2020 Jul 22;20(15):4079. doi: 10.3390/s20154079.
The most commonly used method of fetal monitoring is based on heart activity analysis. Computer-aided fetal monitoring system enables extraction of clinically important information hidden for visual interpretation-the instantaneous fetal heart rate (FHR) variability. Today's fetal monitors are based on monitoring of mechanical activity of the fetal heart by means of Doppler ultrasound technique. The FHR is determined using autocorrelation methods, and thus it has a form of evenly spaced-every 250 ms-instantaneous measurements, where some of which are incorrect or duplicate. The parameters describing a beat-to-beat FHR variability calculated from such a signal show significant errors. The aim of our research was to develop new analysis methods that will both improve an accuracy of the FHR determination and provide FHR representation as time series of events. The study was carried out on simultaneously recorded (during labor) Doppler ultrasound signal and the reference direct fetal electrocardiogram Two subranges of Doppler bandwidths were separated to describe heart wall movements and valve motions. After reduction of signal complexity by determining the Doppler ultrasound envelope, the signal was analyzed to determine the FHR. The autocorrelation method supported by a trapezoidal prediction function was used. In the final stage, two different methods were developed to provide signal representation as time series of events: the first using correction of duplicate measurements and the second based on segmentation of instantaneous periodicity measurements. Thus, it ensured the mean heart interval measurement error of only 1.35 ms. In a case of beat-to-beat variability assessment the errors ranged from -1.9% to -10.1%. Comparing the obtained values to other published results clearly confirms that the new methods provides a higher accuracy of an interval measurement and a better reliability of the FHR variability estimation.
最常用的胎儿监测方法基于胎心活动分析。计算机辅助胎儿监测系统能够提取隐藏在视觉解释中的临床重要信息——瞬时胎儿心率（FHR）变异性。如今的胎儿监护仪基于多普勒超声技术监测胎儿心脏的机械活动。FHR 通过自相关方法确定，因此它具有均匀间隔的形式——每 250 毫秒进行一次瞬时测量，其中一些测量值是不正确的或重复的。从这样的信号计算的描述逐拍 FHR 变异性的参数显示出显著的误差。我们研究的目的是开发新的分析方法，既可以提高 FHR 测定的准确性，又可以提供 FHR 作为事件时间序列的表示。该研究是在同时记录（分娩期间）的多普勒超声信号和参考直接胎儿心电图上进行的。将多普勒带宽的两个子范围分开以描述心脏壁运动和瓣膜运动。通过确定多普勒超声包络来降低信号复杂度后，对信号进行分析以确定 FHR。使用梯形预测函数支持的自相关方法。在最后阶段，开发了两种不同的方法来提供作为事件时间序列的信号表示：第一种方法使用重复测量的校正，第二种方法基于瞬时周期性测量的分段。因此，它确保了平均心跳间隔测量误差仅为 1.35 毫秒。在逐拍变异性评估中，误差范围为-1.9%至-10.1%。将获得的值与其他已发表的结果进行比较，清楚地证实了新方法提供了更高的间隔测量精度和更可靠的 FHR 变异性估计。
