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    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
    Abstract
    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... 

    Comparison of ECG fiducial point extraction methods based on dynamic bayesian network

    , Article 2017 25th Iranian Conference on Electrical Engineering, ICEE 2017, 2 May 2017 through 4 May 2017 ; 2017 , Pages 95-100 ; 9781509059638 (ISBN) Akhbari, M ; Shamsollahi, M. B ; Jutten, C ; Sharif University of Technology
    Abstract
    Cardiovascular diseases are one of the major causes of mortality in humans. One way to diagnose heart diseases and abnormalities is processing of cardiac signals such as electrocardiogram (ECG) signal. In many ECG analysis, location of peak, onset and offset of ECG waves must be extracted as a preprocessing step. These points are called ECG fiducial points (FPs) and convey clinically useful information. In this paper, we compare some FP extraction methods including three methods proposed recently by our research team. These methods are based on extended Kalman filter (EKF), hidden Markov model (HMM) and switching Kalman filter (SKF). Results are given for ECG signals of QT database. For all... 

    ECG fiducial point extraction using switching Kalman filter

    , Article Computer Methods and Programs in Biomedicine ; Volume 157 , 2018 , Pages 129-136 ; 01692607 (ISSN) Akhbari, M ; Montazeri Ghahjaverestan, N ; Shamsollahi, M. B ; Jutten, C ; Sharif University of Technology
    Elsevier Ireland Ltd  2018
    Abstract
    In this paper, we propose a novel method for extracting fiducial points (FPs) of the beats in electrocardiogram (ECG) signals using switching Kalman filter (SKF). In this method, according to McSharry's model, ECG waveforms (P-wave, QRS complex and T-wave) are modeled with Gaussian functions and ECG baselines are modeled with first order auto regressive models. In the proposed method, a discrete state variable called “switch” is considered that affects only the observation equations. We denote a mode as a specific observation equation and switch changes between 7 modes and corresponds to different segments of an ECG beat. At each time instant, the probability of each mode is calculated and...