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    Multi-channel electrocardiogram denoising using a Bayesian filtering framework

    , Article 2006 Computers in Cardiology, CIC, Valencia, 17 September 2006 through 20 September 2006 ; Volume 33 , 2006 , Pages 185-188 ; 02766574 (ISSN); 1424425328 (ISBN); 9781424425327 (ISBN) Sameni, R ; Shamsollahi, M. B ; Jutten, C ; Sharif University of Technology
    In some recent works, model-based filtering approaches have been proved as effective methods for extracting ECG signals from single channel noisy recordings. The previously developed methods, use a highly realistic nonlinear ECG model for the construction of Bayesian filters. In this work, a multi-channel extension of the previous approach is developed, by using a three dimensional model of the cardiac dipole vector. The results have considerable improvement compared with the single channel approach. The method is hence believed to be applicable to low SNR multi-channel recordings  

    Switching kalman filter based methods for apnea bradycardia detection from ECG signals

    , Article Physiological Measurement ; Volume 36, Issue 9 , 2015 , Pages 1763-1783 ; 09673334 (ISSN) Ghahjaverestan, N. M ; Shamsollahi, M. B ; Ge, D ; Hernandez, A. I ; Sharif University of Technology
    Apnea bradycardia (AB) is an outcome of apnea occurrence in preterm infants and is an observable phenomenon in cardiovascular signals. Early detection of apnea in infants under monitoring is a critical challenge for the early intervention of nurses. In this paper, we introduce two switching Kalman filter (SKF) based methods for AB detection using electrocardiogram (ECG) signal. The first SKF model uses McSharry's ECG dynamical model integrated in two Kalman filter (KF) models trained for normal and AB intervals. Whereas the second SKF model is established by using only the RR sequence extracted from ECG and two AR models to be fitted in normal and AB intervals. In both SKF approaches, a... 

    Synthetic ECG generation and bayesian filtering using a Gaussian wave-based dynamical model

    , Article Physiological Measurement ; Volume 31, Issue 10 , 2010 , Pages 1309-1329 ; 09673334 (ISSN) Sayadi, O ; Shamsollahi, M. B ; Clifford, G. D ; Sharif University of Technology
    In this paper, we describe a Gaussian wave-based state space to model the temporal dynamics of electrocardiogram (ECG) signals. It is shown that this model may be effectively used for generating synthetic ECGs as well as separate characteristic waves (CWs) such as the atrial and ventricular complexes. The model uses separate state variables for each CW, i.e. P, QRS and T, and hence is capable of generating individual synthetic CWs as well as realistic ECG signals. The model is therefore useful for generating arrhythmias. Simulations of sinus bradycardia, sinus tachycardia, ventricular flutter, atrial fibrillation and ventricular tachycardia are presented. In addition, discrete versions of...