New Method for Beat-to-Beat Fetal Heart Rate Measurement Using Doppler Ultrasound Signal

Abstract

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.

Impact of maternal posture on fetal physiology in human pregnancy: a narrative review

“…From a gravitational perspective, it is likely that the placental position is relevant after 26 weeks when the specific gravity is such that the fetus' apparent weight is 0.6-0.8 of its actual weight (Sekulić et al, 2005) and, for example, a fetus with a posterior placenta would be resting on top of its placenta when its mother is lying supine. Second, we suggest that future research pertaining to maternal postural-dependent FHR changes should include beat-to-beat fHRV, which can yield insight into fetal autonomic tone that is not otherwise possible by analyzing FHR tracing morphology alone (Shuffrey et al, 2019;Kupka et al, 2020). On a related note, we encourage other innovative approaches like that of Stone et al and their investigation of the FBS with maternal postural changes (Stone et al, 2017).…”

The Effect of Lost Data on the IoT Platform on the Formation of Fetal Heart Rate Graphs for Remote Diagnostic Purposes

“…After testing the module, data collection and analysis of the results are carried out to determine the stability and accuracy of making the module. This study also has a goal to analyze the quality of data transmission on data transmission using IoT thinger.io [30][31] [32], in the BPM 60 measurement, there are 120 FHR graphs of data on SD -Card and IoT and then the average is taken from 120 data every 2 minutes 0.14 0.10 Several studies conclude that data monitoring through IoT media and the impact of the risk of missing data will affect the making of diagnoses by doctors [33][15] [5]. it can be concluded from this research that the researcher concludes that the loss of data in this remote monitoring will be very dangerous, because the lost data will affect the actions that will be taken by the doctor.…”

Ultrasound Doppler fetal heart rate detection algorithm analyzesthe correlation between twin selective fetal growth restriction and cord blood SFass fasL level

“… 7 However, because the Doppler detected by the ultrasound Doppler fetal heart rate detector often contains a large amount of messy, large variability, and uneven noise, it will cause a large degree of interference to the calculation of fetal heart rate. 8 , 9 The algorithms currently used for fetal heart rate detection by ultrasound Doppler are mainly divided into autocorrelation and short-term average amplitude difference method. 10 The autocorrelation algorithm was adopted in this study to process the ultrasound Doppler of fetal heart rate, and the results showed that it can be used for the onset of fetal growth restriction during pregnancy, which provides a reference for understanding the degree of fetal growth restriction.…”