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Articles by A. Azemi
Total Records ( 2 ) for A. Azemi
  H. Gholizade-Narm , A. Azemi , M. Khademi and M. Karimi-Ghartemani
  In this study a synchronization method is developed to prevent the blocking arrhythmias which are caused by lack of synchronization between the two major heart pacemakers called the Sino-Atrial (SA) node and Atrio-Ventricullar (AV) node. Such pacemakers can be modeled by the Van der Pol oscillators. Feedback linearization method is used in synchronization. Since all states are not always available, they are estimated by a new observer in this research. To design the observer, first we introduce a robust observer for a unique Van der Pol oscillator. The robustness of proposed observer is obtained using gain and phase margins test. The observer variables are such that the error dynamical system is linear time varying and we use describing function method to prove its convergence. This observer is then extended to two unidirectional and bidirectional coupled Van der Pol Oscillators. To prove the stability, a novel nonlinear function structure is introduced to seclude the coupled Van der Pol oscillators to two isolated oscillators. The performance of the proposed method is investigated by numerical simulations.
  Z.S. Dastgheib , A. Azemi , M. Khademi , M. Shajiee , M. Arvaneh , H. Gholizadeh and V.R. Sabzevari
  In this study, a new method will be introduced to find ionic conductance parameters of ventricular cell channels that are part of a reentry loop. These parameters play a significant role in generation and dispersion of a normal action potential and hence ECG signal and formation of a reentry. The dangerous phenomenon reentry, occur when an electrical impulse travels in a circle within the heart, rather than moving outward and then stopping. Depending on the timing, this can produce a sustained abnormal rhythm, a self-limiting burst of supraventricular tachycardia, or a dangerous ventricular tachycardia. Here, a detailed Luo-Rudy model has been used for modeling ventricular myocardium cells and construction of a one-dimensional ring for reentry simulations. The proposed method is based on using Genetic Algorithms to identify the unknown parameters. The advantage of the proposed method over Least Squares parameter estimation approach is provided.
 
 
 
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