Sharif Digital Repository

In this paper, it is shown that the main source of mechanical energy of cardiovascular (CV) system i.e., rhythmic heart contraction is transformed to the oscillations of the CV walls and blood flow, and finally CV acoustical waves. These waves propagate through both blood flow (hemodynamical pathways) and tissues (viscoelastical pathways) toward the skin. Nonetheless, the CV walls could be assumed as the source of acoustical waves, since they act as the interface between blood flows and other tissues including skin. After obtaining the approximate accelerations of CV walls from pressure-flow (PF) models, we also needed to model the viscoelastical pathways until the skin. Some improvements on... 

Low and high valence were induced in 20 male volunteers using two groups of pictures stimuli. Heart response was compared between two groups from RR series extracted from recorded ECG measurements. Mean heart rate and heart rate variability measures including time, frequency and Poincare domain were extracted. The results revealed that HRV triangular index, SDNN and SD2 were the only statistically significant parameters between groups (p<0.05). Mean heart rate and power in LF and HF bands were also different between low and high valence groups however level of significance was not reached. © 2015 CCAL  

We propose a novel inverse method that utilizes a set of data to construct a simple equation that governs the stochastic process for which the data have been measured, hence enabling us to reconstruct the stochastic process. As an example, we analyze the stochasticity in the beat-to-beat fluctuations in the heart rates of healthy subjects as well as those with congestive heart failure. The inverse method provides a novel technique for distinguishing the two classes of subjects in terms of a drift and a diffusion coefficients which behave completely differently for the two classes of subjects, hence potentially providing a novel diagnostic tool for distinguishing healthy subjects from those... 

We compute fractal dimension and permutation entropy for healthy and people who have experienced heart failure. Our result shows that permutation entropy is a suitable approach as well as detrend fluctuation analysis (DFA). The result of DFA shows that the fractal dimensions for healthy and heart failure are different as well as the permutation entropy result. The fluctuation value for permutation entropy for an individual who has experienced heart failure is bigger than for a healthy person. There is some specific change in the interbeat signal of a person who has experienced heart failure, but there is not previous trend for a healthy person  

During recording lung sounds over the chest, heart sounds (HS) are also recorded and interferes with the inteipretation of lung sounds especially at low frequencies. Hence, several methods have been proposed to remove or reduce HS from lung sounds. The first step in most of the methods developed for HS reduction is to localize the segments of lung sounds including HS. In this study a method based on multi-resolution product of lung sounds wavelet coefficients was implemented for HS localization and its performance was compared to that of three methods developed for HS localization. The methods were tested on data from 6 healthy subjects recorded at low (7.5ml/s/kg) and medium (15ml/s/kg)... 

In this paper, we proposed a method based on time-frequency dependent features extracted from Intrinsic Mode Functions (IMFs) and physiological feature such as the number of premature beats (PBs) to predict the onset of Paroxysmal Atrial Fibrillation (PAF) by using electrocardiogram (ECG) signal. To extract IMFs, we used Empirical Mode Decomposition (EMD). In order to predict PAF, we used variance of IMFs of signals, the area under the absolute of IMF curves and the number of PBs, since increasing of all of these parameters are a clear sign of PAF occurrence. We used clinical database which was provided for the 2001 Computer in Cardiology Challenge (CinC). The test set of this database... 

Short-term interaction between heart rate (HR) and physiological measures like blood pressure and respiration reveals relevant information about autonomic nervous system (ANS) function. Complex mathematical models for describing their couplings have been proposed in the literature. However, an accurate estimation of their parameters in an inverse modeling problem is crucial to extract reliable ANS related indices. This study considers a physiologically-based model of the cardiovascular-respiratory system and ANS control that presents the neural and mechanical effects of respiration separately. The estimation method is evaluated on synthetic signals. An accurate estimation of the... 

In some recent works, model-based filtering approaches have been proved as effective methods for extracting ECG signals from single channel noisy recordings. The previously developed methods, use a highly realistic nonlinear ECG model for the construction of Bayesian filters. In this work, a multi-channel extension of the previous approach is developed, by using a three dimensional model of the cardiac dipole vector. The results have considerable improvement compared with the single channel approach. The method is hence believed to be applicable to low SNR multi-channel recordings  

Hemodynamic factors, such as Wall Shear Stress (WSS), play a substantial role in arterial diseases. In the larger arteries, such as the carotid artery, interaction between the vessel wall and blood flow affects the distribution of hemodynamic factors. In the present study, both rigid-wall and deformable-wall models are developed in a 3D numerical simulation to assess the effectiveness of arterial rigidity on worsening hemodynamics, especially WSS. Two different rheological models (Newtonian and CarreauYasuda) have been employed to evaluate the influence of blood, non-Newtonian properties, as well. The importance of vessel wall deformability was compared with the rheological model of blood.... 

Red Blood Cells (RBCs) are the main cells in human blood, with a main role in the mechanical properties of blood as a fluid. Several methods have been improved to simulate the mechanical behavior of RBC in micro-capillaries. Since, in microscopic scales, using discrete models is more preferred than continuum methods, the Moving Particle Semi-Implicit method (MPS), which is a recent innovative particle based method, can simulate micro-fluidic flows based on NavierStokes equations. Although, by recent developments, the MPS method has turned into a considerable tool for modeling blood flow in micro meter dimensions, some problems, such as a commitment to use small time step sizes, still... 

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... 

We present generalizations of our previously published artificial models for generating multi-channel ECG so that the simulation of abnormal rhythms is possible. Using a three-dimensional vectorcardiogram (VCG) formulation, we generate the normal cardiac dipole for a patient using a sum of Gaussian kernels, fitted to real VCG recordings. Abnormal beats are then specified either as new dipoles, or as perturbations of the existing dipole. Switching between normal and abnormal beat types is achieved using a hidden Markov model (HMM). Probability transitions can be learned from real data or modeled by coupling to heart rate and sympathovagal balance. Natural morphology changes form beat-to-beat... 

Myocardial infarction is a major cause of death worldwide and remains a social and healthcare burden. Injectable hydrogels with the ability to locally deliver drugs or cells to the damaged area can revolutionize the treatment of heart diseases. Herein, we formulate a thermo-responsive and injectable hydrogel based on conjugated chitosan/poloxamers for cardiac repair. To tailor the mechanical properties and electrical signal transmission, gold nanoparticles (AuNPs) with an average diameter of 50 nm were physically bonded to oxidized bacterial nanocellulose fibers (OBC) and added to the thermosensitive hydrogel at the ratio of 1% w/v. The prepared hydrogels have a porous structure with open... 

Atherosclerotic plaques and thrombosis are chronic inflammatory complications and the main manifestations of cardiovascular diseases (CVD), the leading cause of death globally. Achieving non/minimal-invasive therapeutic means for these implications in the coronary network is vital and has become an interdisciplinary concern. Accordingly, smart drug delivery systems, specifically based on micro- and nanoparticles, as a promising method to offer non/minimal-invasive therapeutic mechanisms are under active research. Notably, computational models enable us to study, design, and predict treatment strategies based on smart drug delivery systems with less time and cost compared with conventional... 

Objective(s): Bioresorbable scaffolds have been advocated as the new generation in interventional cardiology because they could provide temporary scaffolds and then disappear with resorption. Although, the available stents in clinical trials exhibited biosafety, efficacy, no death, and no apparent thrombosis, Mg-substrate degradation on drug release has not been investigated. Materials and Methods: Therefore, more research has been needed to legitimize the replacement of current stents with Mg-based stents. UV-Vis spectrophotometer, scanning electron microscope (SEM), X-ray diffraction (XRD), pH measurement, H2 evolution, and corrosion tests determined the change in hybrid properties and... 

Conventional models of cardiovascular system frequently lack required detail and focus primarily on the overall relationship between pressure, flow and volume. This study proposes a localized and regional model of the cardiovascular system. It utilizes noninvasive blood flow and pressure seed data and temporal cardiac muscle regional activity to predict the operation of the heart under normal and congestive heart failure conditions. The analysis considers specific regions of the heart, namely, base, mid and apex of left ventricle. The proposed method of parameter estimation for hydraulic electric analogy model is recursive least squares algorithm. Based on simulation results and comparison... 

Cardiovascular disease is one of the most rampant causes of death around the world and was deemed as a major illness in Middle and Old ages. Coronary artery disease, in particular, is a widespread cardiovascular malady entailing high mortality rates. Angiography is, more often than not, regarded as the best method for the diagnosis of coronary artery disease; on the other hand, it is associated with high costs and major side effects. Much research has, therefore, been conducted using machine learning and data mining so as to seek alternative modalities. Accordingly, we herein propose a highly accurate hybrid method for the diagnosis of coronary artery disease. As a matter of fact, the...