Sharif Digital Repository

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... 

In this paper, a novel nonlinear joint dynamical model is presented, which is based on a set of coupled ordinary differential equations of motion and a Gaussian mixture model representation of pulsatile cardiovascular (CV) signals. In the proposed framework, the joint interdependences of CV signals are incorporated by assuming a unique angular frequency that controls the limit cycle of the heart rate. Moreover, the time consequence of CV signals is controlled by the same phase parameter that results in the space dimensionality reduction. These joint equations together with linear assignments to observation are further used in the Kalman filter structure for estimation and tracking. Moreover,...