Key result
New Doppler ultrasound algorithms measure fetal heart intervals within ~1.4 ms of reference direct FECG.
Why the study?
Parameters describing beat-to-beat fetal heart rate variability calculated from standard Doppler ultrasound signals show significant errors due to incorrect or duplicate evenly spaced measurements.
Do new Doppler ultrasound signal processing algorithms (using autocorrelation with a trapezoidal prediction function and event segmentation) improve the accuracy of beat-to-beat fetal heart rate interval and variability measurements compared to standard cardiotocography against a direct fetal ECG reference?
Do new Doppler ultrasound signal processing algorithms (using autocorrelation with a trapezoidal prediction function and event segmentation) improve the accuracy of beat-to-beat fetal heart rate interval and variability measurements compared to standard cardiotocography against a direct fetal ECG reference?
Extracting time-series cardiac events from Doppler ultrasound signals via periodicity segmentation and trapezoidal prediction substantially improves beat-to-beat fetal heart rate variability accuracy over conventional cardiotocography monitors.
Answers are grounded in this paper and cite their sources.
New Doppler algorithms may refine intrapartum heart rate variability assessment; leaves open prospective validation and outcome impact before practice change.
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.
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Kupka et al. (2020) studied Intrapartum fetal heart rate monitoring during labor (n=6). New Doppler ultrasound signal processing methods (D1 using duplicate measurement correction and D2 using segmentation of instantaneous periodicity measurements with autocorrelation and trapezoidal prediction functions) vs. Reference direct fetal electrocardiogram (FECG) and standard built-in fetal monitor cardiotocography (FHR_CTG) software was evaluated on Mean fetal heart interval (Ti) measurement error (|ΔTi|) and relative error in short-term beat-to-beat fetal heart rate variability (STV) indices. New Doppler ultrasound signal processing algorithms achieved a mean fetal heart interval measurement error of 1.35 ms and reduced beat-to-beat variability errors to -1.9% to -10.1% compared to FECG.
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