Why the study?
Does the Hilbert transform method improve fetal QRS detection from magnetocardiography signals compared to ICA or raw signals?
Does the Hilbert transform method improve fetal QRS detection from magnetocardiography signals compared to ICA or raw signals?
The Hilbert transform method provides a robust and automated approach for extracting fetal heart rate from magnetocardiography signals with a very low error rate.
May enable automated fetal QRS detection in magnetocardiography; leaves open prospective clinical validation before practice adoption.
Fetal magnetocardiography provides reliable signals of the fetal heart dynamics with high temporal resolution that can be used in a clinical setting. We present a robust Hilbert transform method for extraction of the fetal heart rate. Our method may be applied to signals derived from a single channel or an array of channels. In the case of multichannel data, the channels can be combined to improve signal-to-noise ratio for the extraction of fetal heart data. The method is inherently insensitive to fetal position or movement and, in addition, can be automated. We demonstrate that the determination of R-wave timing is relatively insensitive to waveform morphology. The method can also be applied if the data were preprocessed by independent component analysis (ICA). We compared the Hilbert method, ICA, ICA + Hilbert, and raw signals and found that the Hilbert method gave the best overall performance. We demonstrated that there were approximately 171 errors in 46,789 fetal heart beats.
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Govindan et al. (2008) studied this question.
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