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Published on: November 22, 2013
Extraction of fetal heart rate from maternal surface ECG with provisions for multiple pregnancies
A Fanelli1, M G Signorini, T Heldt
1Computational Physiology and Clinical Inference Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA. fanelli@mit.edu
Twin pregnancies carry an inherently higher risk than singleton pregnancies due to the increased chances of uterine growth restriction. It is thus desirable to monitor the wellbeing of the fetuses during gestation to detect potentially harmful conditions. The detection of fetal heart rate from the maternal abdominal ECG represents one possible approach for noninvasive and continuous fetal monitoring. Here, we propose a new algorithm for the extraction of twin fetal heart rate signals from maternal abdominal ECG recordings. The algorithm detects the fetal QRS complexes and converts the QRS onset series into a binary signal that is then recursively scanned to separate the contributions from the two fetuses. The algorithm was tested on synthetic singleton and twin abdominal recordings. It achieved an average sensitivity and accuracy for QRS complex detection of 97.5% and 93.6%, respectively.
Twin pregnancies carry an inherently higher risk than singleton pregnancies due to the increased chances of uterine growth restriction. It is thus desirable to monitor the wellbeing of the fetuses during gestation to detect potentially harmful conditions. The detection of fetal heart rate from the maternal abdominal ECG represents one possible approach for noninvasive and continuous fetal monitoring. Here, we propose a new algorithm for the extraction of twin fetal heart rate signals from maternal abdominal ECG recordings. The algorithm detects the fetal QRS complexes and converts the QRS onset series into a binary signal that is then recursively scanned to separate the contributions from the two fetuses. The algorithm was tested on synthetic singleton and twin abdominal recordings. It achieved an average sensitivity and accuracy for QRS complex detection of 97.5% and 93.6%, respectively.
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