Sharif Digital Repository

In this paper we introduce two methods for measuring irregularities in human heartbeat time series (HHTS). First we consider the multi-fractal structure of HHTS to distinguish healthy individuals and from those with congestive heart failure. In this way we modify the Extended Self-Similarity (ESS) method and apply it to HHTS. Our second approach is based on the recursive method, which we use to predict the duration of the next heartbeat by considering a few previous ones. We use standard physiological data and show that these approaches lead to very satisfactory methods to resolve the healthy and CHF individuals. These methods can be used potentially in portable electronic heart alarm... 

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  

An essential requirement for performing robotic assisted surgery on a freely beating heart is a prediction algorithm which can estimate the future trajectory of the heart in the varying heart rate (HR) conditions of real surgery with a high accuracy. In this study, a hybrid amplitude modulation- (AM) and autoregressive- (AR) based algorithm was developed to enable estimating the global and local oscillations of the beating heart, raised from its major and minor physiological activities. The AM model was equipped with an estimator of the heartbeat frequency to compensate for the HR variations. The RMS of the prediction errors of the hybrid algorithm was in the range of 165–361 μm for the... 

Heart rate monitoring using wrist-type using photoplethysmographic (PPG) signals during subjects' intensive exercises is a challenging problem, since signals are strongly affected by motion artifacts caused by unexpected movements. This paper presents a method that uses both time and frequency characteristics of signals; using sparse signal reconstruction for high-resolution spectrum estimation. Experimental results on type data sets recorded from 12 subjects during fast running at peak speed of 15 km/hour. The results have a performance with the average absolute error being 1.80 beat per minute  

This paper presents a low complexity while accurate Heart Rate (HR) estimation technique from signals captured by Photoplethysmographic (PPG) sensors worn on the wrist during intensive physical exercise. Wrist-type PPG signals experience severe Motion Artifacts (MA) that hinder efficient HR estimation especially during intensive physical exercises. To suppress the motion artifacts efficiently, simultaneous 3 dimensional acceleration signals are used as reference MAs. The proposed method achieves an Average Absolute Error (AAE) of 1.19 Beats Per Minute (BPM) on the 12 benchmark PPG recordings in which subjects run at speeds of up to 15 km/h. This method also achieves an AAE of 2.17 BPM on the... 

Analysis of heart rate variability (HRV) is commonly used for characterization of autonomic nervous system. As high frequency (HF, known as the respiratory-related) component of HR, overlaps with the typical low frequency (LF) band when the respiratory rate is low, a reference signal for HF variations would help in better discriminating the LF and HF components of HR. The present study proposes a model for time-varying separation of HRV components as well as estimation of HRV parameters using respiration information. An autoregressive moving average with exogenous input (ARMAX) model of HRV is considered with a parametrically modeled respiration signal as the input. The model parameters are... 

Segmented polyurethane (PU) has proven to be the best biomaterial for artificial heart valves, but the calcification of polyurethane surfaces causes serious problems in long-term implants. This work was undertaken to evaluate the effects of polydimethylsiloxane (PDMS) grafting on the calcification, biocompatibility, and blood compatibility of polyurethane. A grafted polyurethane film was compared with virgin polyurethane surfaces. Physical properties of the samples were examined using different techniques. The hydrophobicity of the polyurethane films increased as a result of silicone modification. The effects of surface modification of polyurethane films on their calcification and fibroblast... 

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... 

This study investigates the effect of body acceleration on human cardiac function. Finite element analysis is conducted to simulate geometrical and mechanical properties of human heart. Heart geometrical modeling in three-dimension is performed by segmentation of cardiac MRI images. The nonlinear mechanical behavior of myocardium is modeled by Mooney-Rivlin, Polynomial, Ogden and Yeoh hyperelastic material models. Stress-strain curves of myocardial tissue are obtained from experimental compression tests on bovine heart samples. The experimental results are employed for the evaluation of material coefficients by the nonlinear least squares method. Among hyperelastic models, the Yeoh model... 

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... 

Heart attack is one of the most common causes of death in the world. Coronary artery disease is the most recognized cause of heart attack whose onset and progression have been attributed to low-density lipoprotein (LDL) passing through the wall of the artery. In this paper, hemodynamic variables as well as the concentration of LDL through the coronary porous artery at the Left Anterior Descending coronary artery (LAD), and its first diagonal branch (D1) under the heart motion investigated using computational simulation. The geometry that has been studied in this paper is the first bifurcation of Left Anterior Descending (LAD) that has been placed on a perimeter of hypothetical sphere... 

PPG based heart rate (HR) monitoring has recently attracted much attention with the advent of wearable devices such as smart watches and smart bands. However, due to severe motion artifacts (MA) caused by wristband stumbles, PPG based HR monitoring is a challenging problem in scenarios where the subject performs intensive physical exercises. This work proposes a novel approach to the problem based on supervised learning by Neural Network (NN). By simulations on the benchmark datasets [1], we achieve acceptable estimation accuracy and improved run time in comparison with the literature. A major contribution of this work is that it alleviates the need to use simultaneous acceleration signals.... 

We describe a method for analyzing the stochasticity in non-stationary data for the beat-to-beat fluctuations in the heart rates of healthy subjects, as well as those with congestive heart failure. The method analyzes the return time series of the data as a Markov process, and computes the Markov time scale, i.e., the time scale over which the data are a Markov process. We also construct an effective stochastic continuum equation for the return series. We show that the drift and diffusion coefficients, as well as the amplitude of the return time series for healthy subjects are distinct from those with CHF. Thus, the method may potentially provide a diagnostic tool for distinguishing healthy... 

Background and aims of the study: Mechanical heart valves (MHV) are widely used to replace dysfunctional and failed heart valves. The bileaflet MHV design is very popular due to its superior hemodynamics. Since their introduction in 1977, the hemodynamics of bileaflet prostheses has been extensively studied. In this study the dynamic behaviour during the closing phase of a bileaflet MHV under normal physiological conditions has been investigated. Methods: Fluid analysis is based on the control volume with moving boundaries in the vicinity of the occluder. Unsteady continuity equation, unsteady momentum equation on the control volume and unsteady Bernoulli's equation have been used to... 

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  

The noninvasive fetal electrocardiogram (ECG) data available from Physionet data bank are suitable for developing fetal heart rate (FHR) detection algorithms. The data have been collected from single subject with a broad range of gestation weeks, and have a total data length of more than 9 hours arranged in 55 data sets. However, there are three additional data features which are currently not directly available from Physionet to facilitate the easy usage of these data: (1) the fetal peak visibility evaluation, (2) the gestation week, and (3) the data length. This article presents an improvement to the data bank by providing the additional features. The required pre-processing of the data is... 

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)...