670: Comparing the fetal ST-segment acquired using a FSE and abdominal sensors

Clifford, Gari D.; Sameni, Reza; Ward, Jay; Robertson, Jim; Pettigrew, Courtenay; Wolfberg, Adam

doi:10.1016/j.ajog.2009.10.535

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To date, the morphological parameters of the fECG and their relationship with the well-being of the fetus are still under study. Researchers have extracted parameters such as the QT-interval [8,10,22] and the STsegment [21,60]. The typical benchmark for these studies is commonly the invasive fECG obtained from the fetal scalp electrodes acquired during labor.…”

Section: Fetal Ecg Morphological Parameter Extractionmentioning

confidence: 99%

Noninvasive Fetal Electrocardiography: Models, Technologies, and Algorithms

Sameni

2020

Innovative Technologies and Signal Processing in Perinatal Medicine

Self Cite

View full text Add to dashboard Cite

The fetal electrocardiogram (fECG) was first recorded from the maternal abdominal surface in the early 1900s. During the past fifty years, the most advanced electronics technologies and signal processing algorithms have been used to convert noninvasive fetal electrocardiography into a reliable technology for fetal cardiac monitoring. In this chapter, the major signal processing techniques, which have been developed for the modeling, extraction and analysis of the fECG from noninvasive maternal abdominal recordings are reviewed and compared with one another in detail. The major topics of the chapter include: 1) the electrophysiology of the fECG from the signal processing viewpoint, 2) the mathematical model of the maternal volume conduction media and the waveform models of the fECG acquired from body surface leads, 3) the signal acquisition requirements, 4) model-based techniques for fECG noise and interference cancellation, including adaptive filters and semi-blind source separation techniques, and 5) recent algorithmic advances for fetal motion tracking and online fECG extraction from few number of channels.

show abstract