Search for: heart-rate-variability
Article 42nd Computing in Cardiology Conference, CinC 2015, 6 September 2015 through 9 September 2015 ; Volume 42 , 2015 , Pages 1057-1060 ; 23258861 (ISSN); 9781509006854 (ISBN) ; Moharreri, S ; Jafarnia Dabanloo, N ; Parvaneh, S ; Sharif University of Technology
IEEE Computer Society 2015
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
Article Computers in Biology and Medicine ; Volume 89 , 2017 , Pages 355-367 ; 00104825 (ISSN) ; Zahedi, E ; Zarzoso, V ; Sharif University of Technology
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...
Two statistical methods for resolving healthy individuals and those with congestive heart failure based on extended self-similarity and a recursive method, Article Journal of Biological Physics ; Volume 32, Issue 6 , 2006 , Pages 489-495 ; 00920606 (ISSN) ; Livari, M. A ; Kaviani, K ; Rahimi Tabar , M. R ; Sharif University of Technology
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...
Heart Arrhythmia Classification based on Nonlinear Analysis and Dynamic Behavior of Heart Rate Variability (HRV)Signal, M.Sc. Thesis Sharif University of Technology ; Bagheri Shouraki, Saeed ; Ghorshi, Mohammad Ali
Detection and classification of arrhythmia is important especially for patients in Emergency care units. Early diagnosis of cardiac arrhythmia makes it possible to choose appropriate anti arrhythmic drugs, and is thus very important for improving arrhythmia therapy. Computer-Assisted Diagnostic (CAD) Systems are used in recent decades in which extracted features and classifiers are the most important factor. In this project, we try to focus on both of these two major factors in heart arrhythmia classification using HRV signal. Therefore, in this project, we try to classify different groups of arrhythmia using HRV signal processing especially the nonlinear processing. Our main aim is to...
A hybrid algorithm for prediction of varying heart rate motion in computer-assisted beating heart surgery, Article Journal of Medical Systems ; Volume 42, Issue 10 , 2018 ; 01485598 (ISSN) ; Farahmand, F ; Vossoughi, G ; Alizadeh Ghavidel, A ; Sharif University of Technology
Springer New York LLC 2018
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...
M.Sc. Thesis Sharif University of Technology ; Shamsollahi, Mohammad Bagher
About 42 percent of annual mortality in all around the world is originated from cardiovascular arrhythmias and diseases. One of these arrhythmias is atrial fibrillation whose onset and persistence can produce clot and consequently cause stroke. The basis of our research are upon this idea that dangerous heart arrhythmias do not happen abruptly and there always are some background signs before occurrence of them. In our approach to predict the onset of atrial fibrillation, by analyzing ECG signal in order to extract distinguishing features, we want to classify signals which will terminate Paroxysmal Atrial Fibrillation (PAF) from signals which won’t end with PAF. In this thesis, we propose...
Designing the FPGA-based system for Triangle Phase space Mapping (TPSM) of heart rate variability (HRV) signal, Article 2015 38th International Conference on Telecommunications and Signal Processing, TSP 2015, 9 July 2015 through 11 July 2015 ; July , 2015 , Page(s): 1 - 4 ; 9781479984985 (ISBN) ; Moharreri, S ; Ghorshi, A ; Molnar K ; Herencsar N ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc 2015
There has been an increasing interest in telemonitoring thanks to the availability of new technologies for data transmission and processing with better performances and lower costs. In this paper, we try to develop and implement the HRV signal processing into a Field Programmable Gate Array (FPGA). The hardware implementing algorithm was developed in Verilog Hardware Description Language (HDL). In designed hardware, after defining the number of samples in the input, we extract and analyses the Triangular Phase Space Mapping (TPSM), a novel method for representation of heart rate. The performance of the system was tested using MATLAB and validated based on the input signals
Article Computers in Cardiology 2008, CAR, Bologna, 14 September 2008 through 17 September 2008 ; Volume 35 , 2008 , Pages 773-776 ; 02766574 (ISSN); 1424437067 (ISBN); 9781424437061 (ISBN) ; Nemati, S ; Sameni, R ; Sharif University of Technology
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...