Relevant bibliographies by topics / Aliev-Panfilov model

Academic literature on the topic 'Aliev-Panfilov model'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "Aliev-Panfilov model"

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Grigoriev, Michael, and Nikita V. Turushev. "Computer Simulation of Cardiac Electrical Activity Using an Electrocardiograph on Nanosensors." Advanced Materials Research 1040 (September 2014): 928–32. http://dx.doi.org/10.4028/www.scientific.net/amr.1040.928.

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The problems related to cardiovascular diseases are considered. The method to solve some of the problems has been proposed. We also consider a two-component Aliev-Panfilov model and the algorithm of the hardware-software complexes. The obtained results are presented.
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Sakaguchi, Hidetsugu, and Yasuhiro Nakamura. "Elimination of Breathing Spiral Waves in the Aliev–Panfilov Model." Journal of the Physical Society of Japan 79, no. 7 (July 15, 2010): 074802. http://dx.doi.org/10.1143/jpsj.79.074802.

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Zemlyanukhin, A. I., and A. V. Bochkarev. "Analytical properties and exact solution of the Aliev-Panfilov model." Journal of Physics: Conference Series 1205 (April 2019): 012060. http://dx.doi.org/10.1088/1742-6596/1205/1/012060.

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Beheshti, M., F. H. Foomany, K. Magtibay, S. Masse, P. Lai, J. Asta, D. A. Jaffray, K. Nanthakumar, S. Krishnan, and K. Umapathy. "Modeling Current Density Maps Using Aliev–Panfilov Electrophysiological Heart Model." Cardiovascular Engineering and Technology 7, no. 3 (June 29, 2016): 238–53. http://dx.doi.org/10.1007/s13239-016-0271-0.

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Pavel’chak, I. A., and S. R. Tuikina. "Numerical solution of an inverse problem for the modified aliev–panfilov model." Computational Mathematics and Modeling 24, no. 1 (January 2013): 14–21. http://dx.doi.org/10.1007/s10598-013-9155-4.

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Sakaguchi, Hidetsugu, and Yusuke Kido. "Suppression of Spiral Chaos by a Guiding Network in the Aliev-Panfilov Model." Progress of Theoretical Physics Supplement 161 (2006): 332–35. http://dx.doi.org/10.1143/ptps.161.332.

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Seyedebrahimi, M. Mehdi, and Yesim Serinagaoglu. "Simulation of Transmembrane Potential Propagation in Normal and Ischemic Tissue Using Aliev-Panfilov Model." International Journal of Bioscience, Biochemistry and Bioinformatics 7, no. 1 (2017): 13–19. http://dx.doi.org/10.17706/ijbbb.2017.7.1.13-19.

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Pongui Ngoma, D. V., V. D. Mabonzo, L. J. P. Gomat, G. Nguimbi, and B. B. Bamvi Madzou. "PARAMETER IDENTIFICATION PROBLEM TO FIND THE CARDIAC POTENTIAL WAVE FORM IN IONIC MODELS." Advances in Mathematics: Scientific Journal 11, no. 11 (November 2, 2022): 991–1017. http://dx.doi.org/10.37418/amsj.11.11.2.

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In this paper, we have defined an optimization problem allowing to directly find the shape of the cardiac wave of some ionic models. This allowed us to compare some of these ionic models via a parameter identification problem instead of comparing them directly by plotting the graphs for given values of the parameters. Compared to the empirical methods used to adjust one or two parameters at a time encountered in electrophysiology, we believe that our parameter identification approach is reliable and able to simultaneously identify four to eleven parameters of an ionic model. Using this approach, we adjusted the parameters of the Mitchell-Schaeffer and Aliev-Panfilov models to recover the shape of the action potential obtained experimentally by fluorescence.
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Pravdin, Sergei F., Timofei I. Epanchintsev, Timur V. Nezlobinskii, and Alexander V. Panfilov. "Induced drift of scroll waves in the Aliev–Panfilov model and in an axisymmetric heart left ventricle." Russian Journal of Numerical Analysis and Mathematical Modelling 35, no. 5 (October 27, 2020): 273–83. http://dx.doi.org/10.1515/rnam-2020-0023.

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AbstractThe low-voltage cardioversion-defibrillation is a modern sparing electrotherapy method for such dangerous heart arrhythmias as paroxysmal tachycardia and fibrillation. In an excitable medium, such arrhythmias relate to appearance of spiral waves of electrical excitation, and the spiral waves are superseded to the electric boundary of the medium in the process of treatment due to high-frequency stimulation from the electrode. In this paper we consider the Aliev–Panfilov myocardial model, which provides a positive tension of three-dimensional scroll waves, and an axisymmetric model of the left ventricle of the human heart. Two relations of anisotropy are considered, namely, isotropy and physiological anisotropy. The periods of stimulation with an apical electrode are found so that the electrode successfully entrains its rhythm in the medium, the spiral wave is superseded to the base of the ventricle, and disappears. The results are compared in two-dimensional and three-dimensional media. The intervals of effective stimulation periods are sufficiently close to each other in the two-dimensional case and in the anatomical model. However, the use of the anatomical model is essential in determination of the time of superseding.
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Pavel’chak, I. A. "Numerical Method of Determining a Localized Initial Cardiac Excitation for the Aliev–Panfilov Model from Measurements on the Inner Boundary." Computational Mathematics and Modeling 25, no. 3 (June 14, 2014): 351–55. http://dx.doi.org/10.1007/s10598-014-9231-4.

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Dissertations / Theses on the topic "Aliev-Panfilov model"

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Rajany, K. V. "Numerical Studies of Spiral- and Scroll-wave Dynamics in Cardiac Tissue: (1) Spiral- and Scroll-Wave Turbulence; (2) Spiral- and Scroll-Wave dynamics in Anatomically and Physiologically realistic Mathematical Models for Canine and Human Ventricular Tissue." Thesis, 2019. https://etd.iisc.ac.in/handle/2005/5000.

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A summary of the main results of our studies is given below. In most of our work, we use three mathematical models for cardiac myocytes, namely, the Panfilov model, the Aliev-Panfilov model, and the Hund-Rudy-Dynamic (HRD) canine-ventricular model for our simulations. The first two are two-variable models; the HRD model is a realistic multi-variable complicated model with 45 variables; in a few cases we also employ the TP06 human-ventricular model. The equations for the first two models are given in Chapter 2. The full descriptions of the HRD model and the TP06 model equations are given in Appendices A and B, respectively. In Appendix C, we give a brief explanation of the phase-field method that we have used in our DNS’s to handle boundary conditions.
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Conference papers on the topic "Aliev-Panfilov model"

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Son, Jeongeun, Yuncheng Du, and Dongping Du. "Propagation of Parametric Uncertainty in Aliev-Panfilov Model of Cardiac Excitation." In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2018. http://dx.doi.org/10.1109/embc.2018.8513608.

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Das, Sampad, Nasrin Sultana, Md Ariful Islam Arif, and M. Osman Gani. "Bifurcation analysis of periodic action potentials of cardiac excitation in the Aliev-Panfilov model." In 2016 International Conference on Medical Engineering, Health Informatics and Technology (MediTec). IEEE, 2016. http://dx.doi.org/10.1109/meditec.2016.7835378.

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Wong, Jonathan, Serdar Göktepe, and Ellen Kuhl. "Computational Simulation of Traveling Arrhythmic Waves in Myocardial Tissue." In ASME 2009 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2009. http://dx.doi.org/10.1115/sbc2009-206552.

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Cardiac arrhythmias are common cardiac disorders characterized by irregular electrical activity of the heart. Each year in the United States alone, about half a million deaths and 835,000 hospital discharges result from arrhythmias. In fact, atrial fibrillation is responsible for 15–20% of all ischemic strokes [1]. Due to the complexity of the electrical conduction pathways in myocardium, computational models are useful platforms for gaining insight into the origin of arrhythmias, as well as the development of corrective options. For these purposes, a quantitative finite element model based on the phenomenological Aliev and Panfilov model [2] was implemented to characterize the electrical behavior of cardiac tissue. Several examples of simulated re-entrant spiral waves demonstrate that our implementation can indeed capture the electrical aspects of cardiac tissue.
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