A heterogeneous coupled oscillator model for simulation of ECG signals

Ryzhii, Elena; Ryzhii, M.

doi:10.1016/j.cmpb.2014.04.009

Cited by 46 publications

(49 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In this paper, we provide a system that allows generating an ECG signal using Ryzhii model [30] without knowing the details of differential equations. Although the mathematical model is a powerful tool for modeling the electrical and mechanical activity of the heart, its use is limited to those familiar with the differential equations that describe the system.…”

Section: Discussionmentioning

confidence: 99%

“…In particular, we used the following experimental parameters: a 1 = 40, a 2 = 50, a 3 = 50, a 1 = 40, u 11 = 0.83, u 21 The activation currents I i represent the coupling between the SA and AT muscle and between HP pacemaker and VN muscles. Concerning the Ryzhii model [30], we adjusted the activation currents for the QRS complex and T wave to consider HP oscillator composed by the RB and LB oscillators:…”

Section: A Electrocardiographic Signalmentioning

confidence: 99%

“…To answer this question, we implemented the mathematical model of Ryzhii [30] in the Simulink environment. In the first step, we looked which mathematical constant or variable of the model allows modifying the amplitude and the temporal intervals of the ECG waves in according to the Table.1.…”

Section: Fig 3 Relationship Between Ecg Waves Features and Heart Modmentioning

confidence: 99%

“…In fact, they allow modulating the amplitude of transmembrane ionic currents I ATDe and I VNRe which represent the couplings between the SA ad HP pacemakers and AT and VN muscles. [20,30] To control the time interval between waves (PR, RR, STinterval) we used the coupling coefficients. They provide proper synchronization behavior of pacemakers in a wide range of heart rhythms.…”

Section: Parameters Obtained Through the Neural Networkmentioning

confidence: 99%

“…In the last years, the characterization of electrical muscle responses was proposed by Ryzhii [29] using a quiescent excitable FitzHugh-Nagumo-type (FHN) oscillators. Successively, Ryzhii improved their model including a description for depolarization and repolarization waves of the atrias and ventricles utilizing different modified FHN systems for each ECG waves [30]. The advanced model was able to generate normal ECG signal and several well-known rhythm disorders.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Relationship between Mathematical Parameters of Modified Van der Pol Oscillator Model and ECG Morphological Features

Silvestri¹,

Acciarito²,

Khanal³

2019

Int. J. Adv. Sci. Eng. Inf. Technol.

View full text Add to dashboard Cite

The mathematical model describes the electrical and mechanical activity of the cardiac conduction system thought set of differential equations. By changing the value of parameters included in these equations, it is possible to change the amplitude and the period of ECG waves. Although this model is a powerful tool for modeling the electrical activity of the heart, its use is often limited to those familiar with the differential equations that describe the system. The purpose of this work is to provide a system that allows generating an ECG signal using Ryzhii model without knowing the details of differential equations. First, we provide the relationships between the ECG wave features and the model parameters; then we generalize them through fitting neural networks. Finally, putting in series fitting neural network and heart model, we provide a system that allows generating a synthetic signal by setting as input only the morphological ECG feature. We computed numerical simulation in Simulink environment and implemented the fitting neural networks in Matlab. Results show that non-linear trends characterize the correlation functions between ECG morphological features and model parameters and that the fitting neural networks can generalized this trend by providing the model parameters given in input the respectively ECG feature.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: A Electrocardiographic Signalmentioning

confidence: 99%

Section: Fig 3 Relationship Between Ecg Waves Features and Heart Modmentioning

confidence: 99%

Section: Parameters Obtained Through the Neural Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Relationship between Mathematical Parameters of Modified Van der Pol Oscillator Model and ECG Morphological Features

Silvestri¹,

Acciarito²,

Khanal³

2019

Int. J. Adv. Sci. Eng. Inf. Technol.

View full text Add to dashboard Cite

show abstract

Hopf Bifurcation Analysis of the BVAM Model for Electrocardiogram

Naseer,

Akhtar,

Hajj

2024

NODYCON Conference Proceedings Series

View full text Add to dashboard Cite

ECG model parameters optimization and space state reconstruction

Lopes

Gois

2018

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

The paper proposes a parameter optimization of a three-coupled oscillator model representing cardiac rhythm. First was detected a set of parameters which has a high or low influence on ECG signal. Then was selected a set of parameters that cause a difference in HRV signal. Hence, five parameters of Sinoatrial oscillator were designed for estimating. The optimization by particle swarm with inertia actualization presented parameters which created an ECG signal closer than real ECG. Afterward, in order to compare the ECG model with a normal ECG, the space state of a real ECG signal was reconstructed using two techniques: delay coordinates embedding and singular values decomposition (SVD). The results showed the feasibility of parameter optimization on ECG model and the benefits of using SVD to reconstruct the space state instead of delay coordinates method in this case of ECG signal.

show abstract

A heterogeneous coupled oscillator model for simulation of ECG signals

Cited by 46 publications

References 37 publications

Relationship between Mathematical Parameters of Modified Van der Pol Oscillator Model and ECG Morphological Features

Relationship between Mathematical Parameters of Modified Van der Pol Oscillator Model and ECG Morphological Features

Hopf Bifurcation Analysis of the BVAM Model for Electrocardiogram

ECG model parameters optimization and space state reconstruction

Contact Info

Product

Resources

About