Papers by Minimol Balakrishnan
International journal of medical engineering and informatics, 2024
Brain Sciences, Sep 13, 2023
1) Background and Objective: Alzheimer's disease (AD) is commonly accompanied by autonomic dysfun... more 1) Background and Objective: Alzheimer's disease (AD) is commonly accompanied by autonomic dysfunction. Investigating autonomic dysfunction's occurrence patterns and severity may aid in making a distinction between different dementia subtypes, as cardiac autonomic dysfunction and AD severity are correlated. Heart rate variability (HRV) allows for a non-invasive assessment of the autonomic nervous system (ANS). AD is characterized by cholinergic depletion. A computational model of ANS based on the kinetics of acetylcholine and norepinephrine is used to simulate HRV for various autonomic states. The model has the flexibility to suitably modulate the concentration of acetylcholine corresponding to different autonomic states. (2) Methods: Twenty clinically plausible AD patients are compared to 20 age-and gender-matched healthy controls using HRV measures. Statistical analysis is performed to identify the HRV parameters that vary significantly in AD. By modulating the acetylcholine concentration in a controlled manner, different autonomic states of Alzheimer's disease are simulated using the ANS model. (3) Results: In patients with AD, there is a significant decrease in vagal activity, sympathovagal imbalance with a dominant sympathetic activity, and change in the time domain, frequency domain, and nonlinear HRV characteristics. Simulated HRV features corresponding to 10 progressive states of AD are presented. (4) Conclusions: There is a significant difference in the HRV features during AD. As cholinergic depletion and autonomic dysfunction have a common neurological basis, autonomic function assessment can help in diagnosis and assessment of AD. Quantitative models may help in better comprehending the pathophysiology of the disease and assessment of its progress.
This article was submitted to
2019 Computing in Cardiology Conference (CinC), 2019
Heart Rate Variability (HRV) is the subtle beat to beat changes in heart rate. Autonomic Nervous ... more Heart Rate Variability (HRV) is the subtle beat to beat changes in heart rate. Autonomic Nervous System (ANS) regulates heart rate by controlling the neurotransmitters, mainly Norepinephrine (NE) and Acetyl choline (Ach) from sympathetic and parasympathetic branches respectively. HRV analysis is a noninvasive tool for assessing the integrity of ANS. HRV changes are observed in the onset of heart disease and in a number of disease conditions like sleep apnea, psychiatric disorders, diabetes, hypertension etc. An understanding of the relationship between kinetics at sympathetic and parasympathetic sites and HRV helps to identify biological changes associated with various autonomic imbalance conditions and hence help in targeted diagnosis and therapy. A computational model of ANS for heart rate regulation is proposed in this study. Fitzhugh Nagumo (FHN) model is used as the successive stage of proposed model to generate a discrete time heart beat interval series. HRV data from a group of healthy individuals having balanced sympathetic and parasympathetic activities were studied. The results were in agreement with parameters derived from model synthesized data for the same autonomic state.
Frontiers in Physiology, 2015
Simulation studies of cardiac arrhythmias at the whole heart level with electrocardiogram (ECG) g... more Simulation studies of cardiac arrhythmias at the whole heart level with electrocardiogram (ECG) gives an understanding of how the underlying cell and tissue level changes manifest as rhythm disturbances in the ECG. We present a 2D whole heart model (WHM2D) which can accommodate variations at the cellular level and can generate the ECG waveform. It is shown that, by varying cellular-level parameters like the gap junction conductance (GJC), excitability, action potential duration (APD) and frequency of oscillations of the auto-rhythmic cell in WHM2D a large variety of cardiac arrhythmias can be generated including sinus tachycardia, sinus bradycardia, sinus arrhythmia, sinus pause, junctional rhythm, Wolf Parkinson White syndrome and all types of AV conduction blocks. WHM2D includes key components of the electrical conduction system of the heart like the SA (Sino atrial) node cells, fast conducting intranodal pathways, slow conducting atriovenctricular (AV) node, bundle of His cells, Purkinje network, atrial, and ventricular myocardial cells. SA nodal cells, AV nodal cells, bundle of His cells, and Purkinje cells are represented by the Fitzhugh-Nagumo (FN) model which is a reduced model of the Hodgkin-Huxley neuron model. The atrial and ventricular myocardial cells are modeled by the Aliev-Panfilov (AP) two-variable model proposed for cardiac excitation. WHM2D can prove to be a valuable clinical tool for understanding cardiac arrhythmias.
A simplified 2D whole heart model (2DWHM) which simulates the Electrocardiogram (ECG) accurately ... more A simplified 2D whole heart model (2DWHM) which simulates the Electrocardiogram (ECG) accurately is presented. Although extremely detailed whole heart 3D models are available, they are computationally expensive. On the other hand most of the 2D cardiac models are homogeneous models aiming at modeling activation propagation in a small patch of cardiac tissue; they are not meant to be whole heart models. A two-dimensional heterogeneous "whole heart" model consisting of an array of specialized cardiac cells, with appropriate anatomical distribution, interacting via gap junction conductance (GJC) is envisioned to be a midway solution to this problem. The proposed 2D whole heart model includes various key components of the electrical conduction system of the heart including the SA (Sino atrial) node, fast conducting inter-atrial pathways, slow conducting AV (atrio-ventricular) node, Bundle of His, Purkinje network, and atrial and ventricular myocardial cells. Atrial and ventric...
Cardiac arrhythmias are defined as disturbances in normal heart rhythm which vary from inconseque... more Cardiac arrhythmias are defined as disturbances in normal heart rhythm which vary from inconsequential to serious life threatening conditions. Simulation studies of cardiac arrhythmias at the whole heart level with electrocardiogram (ECG) gives an understanding how the underlying cell and tissue level changes manifest as rhythm disturbances in the ECG. We present a 2D whole heart model (WHM2D) which can accommodate variations at the cellular level and can generate an ECG waveform. It is shown that, by varying cellular-level parameters like the gap junction conductance (GJC), excitability, action potential duration(APD) and frequency of oscillations of the auto-rhythmic cells in WHM2D a large variety of cardiac arrhythmias can be generated. Sinus tachycardia, sinus bradycardia, sinus arrhythmia, sinus pause, junctional rhythm, Wolf Parkinson White syndrome and AV conduction blocks are thereby simulated. WHM2D includes key components of the electrical conduction system of the heart like the SA (Sino atrial) node cells, fast conducting inter-atrial pathways, slow conducting Atrivenctricular (AV) node, bundleof His cells, Purkinje network, atrial and ventricular myocardial cells. SA nodal cells, AV nodal cells, bundleof His cells and Purkinje cells are represented by the Fitzhugh-Nagumo (FN) model which is a reduced model of the Hodgkin-Huxley neuron model. The atrial and ventricular myocardial cells are modeled by the Aliev-Panfilov (AP) two-variable model proposed for cardiac excitation. WHM2D can prove to be a valuable clinical tool for understanding cardiac arrhythmias.
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Papers by Minimol Balakrishnan