Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive pattern recognition in the analysis of cardiotocographic records
IEEE Transactions on Neural Networks
A robust approach to independent component analysis of signals with high-level noise measurements
IEEE Transactions on Neural Networks
Computers in Biology and Medicine
Expert Systems with Applications: An International Journal
Research of fetal ECG extraction using wavelet analysis and adaptive filtering
Computers in Biology and Medicine
Atrial activity selection for atrial fibrillation ECG recordings
Computers in Biology and Medicine
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In this paper, an algorithm based on independent component analysis (ICA) for extracting the fetal heart rate (FHR) from maternal abdominal electrodes is presented. Three abdominal ECG channels are used to extract the FHR in three steps: first preprocessing procedures such as DC cancellation and low-pass filtering are applied to remove noise. Then the algorithm for multiple unknown source extraction (AMUSE) algorithm is fed to extract the sources from the observation signals include fetal ECG (FECG). Finally, FHR is extracted from FECG. The method is shown to be capable of completely revealing FECG R-peaks from observation leads even with a SNR=-200dB using semi-synthetic data.