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Article title METHODS OF FILTRATION OF MATERNAL AND FETAL ELECTROCARDIOGRAM
Authors Khasheva S., Kalinichenko A.
Section SECTION I. EQUIPMENT AND SOFTWARE OF FUNCTIONAL DIAGNOSTICS AND THERAPY
Month, Year 05, 2008 @en
Index UDC 616.12-073.97
DOI
Abstract Nonlinear Bayesian filtering framework is proposed for the filtering of maternal and fetal electrocardiogram (ECG) recordings. A modified version of the nonlinear dynamic model of the ECG is used in the Kalman Filters The results are far-reaching. This method may therefore serve as an effective framework for the model-based filtering of ECG recordings.

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Keywords electrocardiogram (ECG) recording, diagnostics of fetal, filtering signals.
References 1. Taigang He, Gari Clifford and Lionel Tarassenko Application of Independent component analysis in Removing Artefacts from the ECG // Neural Counting and Applications. – Vol. 15. – 2006, – № 2. –P. 105–106.
2. Sameni R., Shamsollahi M. B., Jutten C., Clifford G. D. A Nonlinear Bayesian Filtering Framework for ECG Denoising // IEEE Transactions On Biomedical Engineering – Vol. 54. – 2007. –№ 12. – P. 2172–2185.
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