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    Dynamic diversity enhancement in particle swarm optimization (DDEPSO) algorithm for preventing from premature convergence

    , Article Procedia Computer Science ; Volume 24 , 2013 , Pages 54-65 ; ISSN: 18770509 Nezami, O. M ; Bahrampour, A ; Jamshidlou, P ; Sharif University of Technology
    2013
    Abstract
    The problem of early convergence in the Particle Swarm Optimization (PSO) algorithm often causes the search process to be trapped in a local optimum. This problem often occurs when the diversity of the swarm decreases and the swarm cannot escape from a local optimal. In this paper, a novel dynamic diversity enhancement particle swarm optimization (DDEPSO) algorithm is introduced. In this variant of PSO, we periodically replace some of the swarm's particles by artificial ones, which are generated based on the history of the search process, in order to enhance the diversity of the swarm and promote the exploration ability of the algorithm. Afterwards, we update the velocity of the artificial... 

    Robust detection of premature ventricular contractions using a wave-based Bayesian framework

    , Article IEEE transactions on bio-medical engineering ; Volume 57, Issue 2 , September , 2010 , Pages 353-362 ; 15582531 (ISSN) Sayadi, O ; Shamsollahi, M. B ; Clifford, G. D ; Sharif University of Technology
    2010
    Abstract
    Detection and classification of ventricular complexes from the ECG is of considerable importance in Holter and critical care patient monitoring, being essential for the timely diagnosis of dangerous heart conditions. Accurate detection of premature ventricular contractions (PVCs) is particularly important in relation to life-threatening arrhythmias. In this paper, we introduce a model-based dynamic algorithm for tracking the ECG characteristic waveforms using an extended Kalman filter. The algorithm can work on single or multiple leads. A "polargram"--a polar representation of the signal--is introduced, which is constructed using the Bayesian estimations of the state variables. The polargram... 

    Switching kalman filter based methods for apnea bradycardia detection from ECG signals

    , Article Physiological Measurement ; Volume 36, Issue 9 , 2015 , Pages 1763-1783 ; 09673334 (ISSN) Ghahjaverestan, N. M ; Shamsollahi, M. B ; Ge, D ; Hernandez, A. I ; Sharif University of Technology
    Abstract
    Apnea bradycardia (AB) is an outcome of apnea occurrence in preterm infants and is an observable phenomenon in cardiovascular signals. Early detection of apnea in infants under monitoring is a critical challenge for the early intervention of nurses. In this paper, we introduce two switching Kalman filter (SKF) based methods for AB detection using electrocardiogram (ECG) signal. The first SKF model uses McSharry's ECG dynamical model integrated in two Kalman filter (KF) models trained for normal and AB intervals. Whereas the second SKF model is established by using only the RR sequence extracted from ECG and two AR models to be fitted in normal and AB intervals. In both SKF approaches, a... 

    Prediction of Heart Arrhythmias Related to Pramature Beats

    , M.Sc. Thesis Sharif University of Technology Sabeti, Elyas (Author) ; Shamsollahi, Mohammad Bagher (Supervisor)
    Abstract
    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... 

    Manifold learning for ECG arrhythmia recognition

    , Article 2013 20th Iranian Conference on Biomedical Engineering, ICBME 2013 ; 2013 , Pages 126-131 Lashgari, E ; Jahed, M ; Khalaj, B ; Sharif University of Technology
    IEEE Computer Society  2013
    Abstract
    Heart is a complex system and we can find its function in electrocardiogram (ECG) signal. The records show high mortality rate of heart diseases. So it is essential to detect and recognize ECG arrhythmias. The problem with ECG analysis is the vast variations among morphologies of ECG signals. Premature Ventricular Contractions (PVC) is a common type of arrhythmia which may lead to critical situations and contains risk. This study, proposes a novel approach for detecting PVC and visualizing data with respect to ECG morphologies by using manifold learning. To this end, the Laplacian Eigenmaps - One of the reduction method and it is in the nonlinear category - is used to extract important... 

    Prediction of Paroxysmal Atrial Fibrillation using Empirical Mode Decomposition and RR intervals

    , Article 2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2012, 17 December 2012 through 19 December 2012 ; December , 2012 , Pages 750-754 ; 9781467316668 (ISBN) Sabeti, E ; Shamsollahi, M. B ; Afdideh, F ; Sharif University of Technology
    2012
    Abstract
    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... 

    Improving the mechanical characteristics of semi-rigid saddle connections

    , Article Journal of Constructional Steel Research ; Volume 186 , 2021 ; 0143974X (ISSN) Moghaddam, H ; Sadrara, A ; Sharif University of Technology
    Elsevier Ltd  2021
    Abstract
    There are many steel structures in Iran with semi-rigid saddle connections. It has been observed that, during a strong earthquake, this type of connection can experience a premature fracture, which will endanger the stability of the structure. The present study endeavored to improve the mechanical characteristics including the initial stiffness, yield moment, maximum moment, crack rotation, and load transfer mechanisms of the conventional saddle connections using retrofitting methods. An experimental study was conducted on six full-scale specimens to study the effect of the retrofitting methods on the stiffness, yield moment, and maximum moment of the connection and for the prevention of... 

    Detection of Apnea Bradycardia from ECG Signals of Preterm Infants Using Layered Hidden Markov Model

    , Article Annals of Biomedical Engineering ; Volume 49, Issue 9 , 2021 , Pages 2159-2169 ; 00906964 (ISSN) Sadoughi, A ; Shamsollahi, M. B ; Fatemizadeh, E ; Beuchée, A ; Hernández, A. I ; Montazeri Ghahjaverestan, N ; Sharif University of Technology
    Springer  2021
    Abstract
    Apnea-bradycardia (AB) is a common complication in prematurely born infants, which is associated with reduced survival and neurodevelopmental outcomes. Thus, early detection or predication of AB episodes is critical for initiating preventive interventions. To develop automatic real-time operating systems for early detection of AB, recent advances in signal processing can be employed. Hidden Markov Models (HMM) are probabilistic models with the ability of learning different dynamics of the real time-series such as clinical recordings. In this study, a hierarchy of HMMs named as layered HMM was presented to detect AB episodes from pre-processed single-channel Electrocardiography (ECG). For... 

    A trainable neural network ensemble for ECG beat classification

    , Article World Academy of Science, Engineering and Technology ; Volume 70 , 2010 , Pages 788-794 ; 2010376X (ISSN) Sajedin, A ; Zakernejad, S ; Faridi, S ; Javadi, M ; Ebrahimpour, R ; Sharif University of Technology
    2010
    Abstract
    This paper illustrates the use of a combined neural network model for classification of electrocardiogram (ECG) beats. We present a trainable neural network ensemble approach to develop customized electrocardiogram beat classifier in an effort to further improve the performance of ECG processing and to offer individualized health care. We process a three stage technique for detection of premature ventricular contraction (PVC) from normal beats and other heart diseases. This method includes a denoising, a feature extraction and a classification. At first we investigate the application of stationary wavelet transform (SWT) for noise reduction of the electrocardiogram (ECG) signals. Then... 

    The effect of improved cooling on the microstructure and mechanical properties of friction stir-welded advanced high-strength dual-phase steel

    , Article Steel Research International ; Volume 92, Issue2 , August , 2020 Mahmoudiniya, M ; Kokabi, A. H ; Goodarzi, M ; Kestens, L. A. I ; Sharif University of Technology
    Wiley-VCH Verlag  2020
    Abstract
    The heat-affected zone (HAZ)softening is considered one of the most significant challenges during welding of ferrite–martensite dual-phase (DP) steels. In fact, the strain localization in the softened area results in a premature fracture that degrades the mechanical properties of the joint. Herein, the objective is to investigate the effectiveness of improved cooling using a high thermal diffusivity backing plate (BP) to reduce HAZ softening and enhance the mechanical properties of friction stir-welded DP700 steel. Accordingly, friction stir butt welding of DP700 steel was conducted using copper and mild steel BPs. The findings show that the replacement of steel BP with copper significantly... 

    The effect of improved cooling on the microstructure and mechanical properties of friction stir-welded advanced high-strength dual-phase steel

    , Article Steel Research International ; Volume 92, Issue 2 , 2021 ; 16113683 (ISSN) Mahmoudiniya, M ; Kokabi, A. H ; Goodarzi, M ; Kestens, L. A. I ; Sharif University of Technology
    Wiley-VCH Verlag  2021
    Abstract
    The heat-affected zone (HAZ) softening is considered one of the most significant challenges during welding of ferrite–martensite dual-phase (DP) steels. In fact, the strain localization in the softened area results in a premature fracture that degrades the mechanical properties of the joint. Herein, the objective is to investigate the effectiveness of improved cooling using a high thermal diffusivity backing plate (BP) to reduce HAZ softening and enhance the mechanical properties of friction stir-welded DP700 steel. Accordingly, friction stir butt welding of DP700 steel was conducted using copper and mild steel BPs. The findings show that the replacement of steel BP with copper significantly... 

    Burden of transport-related injuries in the eastern mediterranean region: A systematic analysis for the global burden of disease study 2017

    , Article Archives of Iranian Medicine ; Volume 24, Issue 7 , 2021 , Pages 512-525 ; 10292977 (ISSN) Safiri, S ; Sullman, M. J. M ; Lajunen, T ; Hill, T ; Almasi Hashiani, A ; Moradi Lakeh, M ; Farzadfar, F ; Sepanlou, S. G ; Abu-Gharbieh, E ; Aghamolaei, T ; Ahmad, T ; Alghnam, S. A ; Al-Hajj, S ; Alipour, V ; Aljunid, S. M ; Anjomshoa, M ; Ansari Moghaddam, A ; Arabloo, J ; Bayati, M ; Bedi, N ; Bendak, S ; Bhutta, Z. A ; Bijani, A ; Dahlawi, S. M. A ; Dianatinasab, M ; Forooshani, Z. S. D ; Elhabashy, H. R ; Zeydi, A. E ; Eskandarieh, S ; Ghafourifard, M ; Ghashghaee, A ; Grivna, M ; Gubari, M. I. M ; Hamadeh, R. R ; Hamidi, S ; Hayat, K ; Rad, E. H ; Hosseinzadeh, M ; Househ, M ; Naghibi, S. S ; Jahani, M. A ; Kalankesh, L. R ; Kalhor, R ; Kamel, I ; Khammarnia, M ; Khan, M ; Khazaie, H ; Komaki, H ; Lahimchi, A ; Madadin, M ; Maleki, S ; Manafi, N ; Mansour Ghanaei, F ; Mansournia, M. A ; Menezes, R. G ; Mohammad, Y ; Mohammadian Hafshejani, A ; Mohebi, F ; Moradi, G ; Moradzadeh, R ; Mousavi, S. M ; Naderi, M ; Nikbakhsh, R ; Pakshir, K ; Pourshams, A ; Rabiee, N ; Rafiei, A ; Rawassizadeh, R ; Rezapour, A ; Saddik, B ; Moghaddam, S. S ; Salamati, P ; Salem, M. R ; Salem, H ; Samy, A. M ; Sathian, B ; Shahabi, S ; Shaikh, M. A ; Shams-Beyranvand, M ; Shamsizadeh, M ; Sobhiyeh, M. R ; Soheili, A ; Tehrani Banihashemi, A ; Waheed, Y ; Yusefzadeh, H ; Moghadam, T. Z ; Zaki, L ; Zamani, M ; Zandian, H ; Malekzadeh, R ; Naghavi, M ; Sharif University of Technology
    Academy of Medical Sciences of I.R. Iran  2021
    Abstract
    Background: Transport-related injuries (TIs) are a substantial public health concern for all regions of the world. The present study quantified the burden of TIs and deaths in the Eastern Mediterranean region (EMR) in 2017 by sex and age. Methods: TIs and deaths were estimated by age, sex, country, and year using Cause of Death Ensemble modelling (CODEm) and DisMod-MR 2.1. Disability-adjusted life years (DALYs), which quantify the total burden of years lost due to premature death or disability, were also estimated per 100 000 population. All estimates were reported along with their corresponding 95% uncertainty intervals (UIs). Results: In 2017, there were 5.5 million (UI 4.9-6.2)... 

    LSTM-Based ecg classification for continuous monitoring on personal wearable devices

    , Article IEEE Journal of Biomedical and Health Informatics ; Volume 24, Issue 2 , 2020 , Pages 515-523 Saadatnejad, S ; Oveisi, M ; Hashemi, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Abstract
    Objective: A novel electrocardiogram (ECG) classification algorithm is proposed for continuous cardiac monitoring on wearable devices with limited processing capacity. Methods: The proposed solution employs a novel architecture consisting of wavelet transform and multiple long short-term memory (LSTM) recurrent neural networks (see Fig. 1). Results: Experimental evaluations show superior ECG classification performance compared to previous works. Measurements on different hardware platforms show the proposed algorithm meets timing requirements for continuous and real-time execution on wearable devices. Conclusion: In contrast to many compute-intensive deep-learning based approaches, the... 

    Homozygous mutations in C14orf39/SIX6OS1 cause non-obstructive azoospermia and premature ovarian insufficiency in humans

    , Article American Journal of Human Genetics ; Volume 108, Issue 2 , 2021 , Pages 324-336 ; 00029297 (ISSN) Fan, S ; Jiao, Y ; Khan, R ; Jiang, X ; Javed, A. R ; Ali, A ; Zhang, H ; Zhou, J ; Naeem, M ; Murtaza, G ; Li, Y ; Yang, G ; Zaman, Q ; Zubair, M ; Guan, H ; Zhang, X ; Ma, H ; Jiang, H ; Ali, H ; Dil, S ; Shah, W ; Ahmad, N ; Zhang, Y ; Shi, Q ; Sharif University of Technology
    Cell Press  2021
    Abstract
    Human infertility is a multifactorial disease that affects 8%–12% of reproductive-aged couples worldwide. However, the genetic causes of human infertility are still poorly understood. Synaptonemal complex (SC) is a conserved tripartite structure that holds homologous chromosomes together and plays an indispensable role in the meiotic progression. Here, we identified three homozygous mutations in the SC coding gene C14orf39/SIX6OS1 in infertile individuals from different ethnic populations by whole-exome sequencing (WES). These mutations include a frameshift mutation (c.204_205del [p.His68Glnfs∗2]) from a consanguineous Pakistani family with two males suffering from non-obstructive... 

    Clinical validation of a smartphone-based handheld ECG device: A validation study

    , Article Critical Pathways in Cardiology ; Volume 21, Issue 4 , 2022 , Pages 165-171 ; 1535282X (ISSN) Ahmadi-Renani, S ; Gharebaghi, M ; Kamalian, E ; Hajghassem, H ; Ghanbari, A ; Karimi, A ; Mansoury, B ; Dayari, M. S ; Khatmi Nemati, M ; Karimi, A ; Zarghami, M. H ; Vasheghani Farahani, A ; Sharif University of Technology
    Lippincott Williams and Wilkins  2022
    Abstract
    Background: Remote cardiac monitoring and screening have already become an integral telemedicine component. The wide usage of several different wireless electrocardiography (ECG) devices warrants a validation study on their accuracy and reliability. Methods: Totally, 300 inpatients with the Nabz Hooshmand-1 handheld ECG device and the GE MAC 1200 ECG system (as the reference) were studied to check the accuracy of the devices in 1 and 6-limb lead performance. Simultaneous 10-second resting ECGs were assessed for the most common ECG parameters in lead I. Afterward, 6-lead ECGs (limb leads), were performed immediately and studied for their morphologies. Results: Of the 300 patients, 297 had...