Journal
PHYSIOLOGICAL MEASUREMENT
Volume 29, Issue 5, Pages 595-613Publisher
IOP PUBLISHING LTD
DOI: 10.1088/0967-3334/29/5/006
Keywords
model-based filtering; ECG/MCG denoising; EEG denoising; EMG denoising; fetal ECG/MCG extraction
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Electrocardiogram (ECG) and magnetocardiogram (MCG) signals are among the most considerable sources of noise for other biomedical signals. In some recent works, a Bayesian filtering framework has been proposed for denoising the ECG signals. In this paper, it is shown that this framework may be effectively used for removing cardiac contaminants such as the ECG, MCG and ballistocardiographic artifacts from different biomedical recordings such as the electroencephalogram, electromyogram and also for canceling maternal cardiac signals from fetal ECG/MCG. The proposed method is evaluated on simulated and real signals.
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