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Determination of Correlation between Phase Amplitude Coupling and Surprise in Brain
, M.Sc. Thesis Sharif University of Technology ; Karblaei Aghajan, Hamid (Supervisor)
Abstract
The human brain needs to create a model of data surrounding it continuously. To do so, handling the dynamics of information through communication between the brain regions is a critical step. Having a model of this procedure in the brain not only provides a clear explanation of how cognition occurs in the brain, but also enables us to have a better view of the cognition impairments in the brain. Surprise is a process in the brain that brings various cognitive abilities, including attention and memory, into practical use. Furthermore, these abilities are about manipulating the input information in an optimized way. Memory is the ability to store information arriving at a specific time....
Investigation into the Effect of Material and Geometrical Parameters on Mechanical Behavior of Medical Guidewire
, M.Sc. Thesis Sharif University of Technology ; Arghavani Hadi, Jamal (Supervisor)
Abstract
Today, tens of millions of people on the planet suffer from heart disease. For the correct diagnosis and treatment of these diseases, there is a vital need for accurate scientific evidence such as various types of vascular and cardiac imaging. One of the applications of guidewires is in cardiovascular imaging. Of course, in addition to diagnosis, this device is also used in the treatment of disease. It should be noted that about 21 million central vessel catheters are performed annually on heart patients, of which about 16 million are performed using the seldinger method. Reportedly, unfortunately, 5% to 19% of these operations have had side effects and harm to the patient or failure....
Fabrication the Hydrogel Microfibers Using Bioprinter with Application in Cardiovascular Model
, M.Sc. Thesis Sharif University of Technology ; Saadatmand, Maryam (Supervisor)
Abstract
Cardiovascular disease (CVD) currently remains a considerable challenge for clinical treatments. CVDs account for N17.5 million deaths per year and will predictably increase to 23.6 million by 2030. The main purpose is to create human model systems to study the effect of disease mutations or drug treatment on the heart. In addition, engineered cardiac tissues are considered promising candidates to be transplanted to improve the function of diseased hearts. For engineered active tissues/organs, 3D bioprinting can fabricate complex tissue architecture with a spatiotemporal distribution of bioactive substances (cells, growth factors, and others) to better guide tissue regeneration. However,...
Diagnosis and Prediction of Coronary Arteries Disease by Applying Data Mining and Image Processing Techniques
, M.Sc. Thesis Sharif University of Technology ; Khedmati, Majid (Supervisor) ; Foroozan Nia, Khalil (Co-Supervisor)
Abstract
Heart disease is one of the major causes of death in all countries, especially developing countries. At the moment, using Image Processing methods as well as analysis of electrocardiographic signals, heart disease is diagnosed with the help of specialists. Applying artificial intelligence and machine learning methods, many studies attempted to provide models that are used to diagnose automatically the heart disease without the need for a specialist and only relying on the past data. But less is done on CTA images of the heart. Hence, in this thesis, a new method for image processing and a Multi Support Vector Machine (MSVM) classification for coronary artery disease detection based on CTA...
Differences of the Brain’s Surprise Response Due to the Habituation Effect in Neurodegenerative Patients and Healthy People
, M.Sc. Thesis Sharif University of Technology ; Karbalaei Aghajan, Hamid (Supervisor)
Abstract
The brain is constantly placed in stochastic environments. This leads to the brain developing a probabilistic model for the environment. However, sometimes unexpected events occur that lead to surprise and a need for updating the probabilistic model. It can be concluded from this argument that reduction in brian’s surprise is a sign of learning. On the other hand, a probability distribution obtained from a probabilistic model contains an amount of uncertainty. Reducing this uncertainty can also be considered a sign of learning. Surprise and uncertainty can be obtained from a probability distribution using information theory concepts. Another important issue in learning is habituation, which...
Detection of Phase Amplitude Coupling Within and Between Different Brain Areas for DBS ON/OFF in Parkinson Disease
, M.Sc. Thesis Sharif University of Technology ; Rabiee, Hamid Reza (Supervisor) ; Manzuri Shalmani, Mohammad Taghi (Supervisor)
Abstract
Recent studies of brain activities indicate that Phase-Amplitude Coupling (PAC) between several regions of the brain, are meaningfully related to Parkinson’s Disease. In this research, we have studied PAC as a statistical measure in Parkinsonian patients’ brains while Deep Brain Stimulation treatment with different stimulation frequencies are being applied. In order to do so, we have investigated patients’ brain signals, and estimated PAC between regions of interest; afterwards, by using the estimated PAC values, we have found significant effects of the treatments on parkinsonian brains; furthermore, two treatments that are using 130 Hz and 340 Hz stimuli signals are compared. In this...
Application of Data Mining Techniques in Diagnosis & Prediction of Heart Disease
, M.Sc. Thesis Sharif University of Technology ; Akhavan Niaki, Taghi (Supervisor)
Abstract
Nowadays, data is the most important asset for health organizations in which the process of collecting, storing and analyzing of data leads to success of health organizations. Many companies have turned to data mining for the beneficial use of these data. The main purpose of data mining is to obtain useful knowledge from existing data. One of the diseases that is very significant for data miners is cardiovascular disease. Cardiovascular disease is the most important cause of death in the world. Therefore, it is necessary to improve the diagnostic and predictive measures of these patients. In this study, a database containing of characteristics of patients with chest pain who referred to...
2-D Modeling of Blood Flow in Mitral Valve During its Closing and Opening
, M.Sc. Thesis Sharif University of Technology ; Firoozabadi, Bahar (Supervisor) ; Saeedi, Mohammad Saeed (Co-Supervisor)
Abstract
Problems with the mitral valve can make the heart less efficient at pumping blood around the body. Severe problems can lead to heart failure if the valve is not surgically repaired or replaced. A simple approximation of the heart geometry is used and the valve dimensions are based on reported measurements. The primary objective for this study is to design and simulate the opening and closing behavior of the mitral valve using 2D fluid-structure interaction (FSI) model using ADINA software in order to evaluate and investigate the hemodynamic performance and problems of mitral valve, in which the blood is described as a viscous incompressible fluid, and the mitral valve is described as an...
Development of a Balance Assessment Method in Dynamic Tasks (LOS) Using a Sway Control Model in Parkinson's Disease
, M.Sc. Thesis Sharif University of Technology ; Behzadipour, Saeed (Supervisor) ; Mohebbi, Abolfazl (Co-Supervisor)
Abstract
Parkinson's disease impairs the patients' balance with the degeneration of the neurons related to their postural control. There are many rehabilitation methods to preclude the disease or weaken its effects. To assess the influence of these methods and their outcome, there are two main evaluation methods, including clinical (qualitative and dependent on the presence of a therapist) and quantitative, such as posturography. Using control models is one of the quantitative methods researchers have been used for more than three decades. Considering this and what have been done in the literature, the purpose of this research is to develop a balance assessment method in dynamic tasks, such as the...
A Quantitative Structure-Activity Relationship Study on Multiple Sclerosis (MS) Drugs
, M.Sc. Thesis Sharif University of Technology ; Jalali-Heravi, Mehdi (Supervisor)
Abstract
In the present work we report a quantitative structure-activity relationship (QSAR) study on S1P1 receptor’s agonists that have therapeutic potential for autoimmune disorders such as Multiple Sclerosis (MS). Such studies play an important role in drug design and lead optimization by developing a mathematical relationship between the chemical structures of compounds and their biological activities.
We used both linear and nonlinear techniques such as MLR and ANN respectively to model these compounds together with techniques such as Stepwise-MLR, GA-MLR and GA-ANN in the variable selection step as it is an important step in every QSAR study. Since topological descriptors are well...
We used both linear and nonlinear techniques such as MLR and ANN respectively to model these compounds together with techniques such as Stepwise-MLR, GA-MLR and GA-ANN in the variable selection step as it is an important step in every QSAR study. Since topological descriptors are well...
Fabrication and Modification of Hollow Fiber Polysulfone Membrane Using Uio-66-NH2 and Mil-125-NH2 Nanoparticles by Mixed Matrix Method
, M.Sc. Thesis Sharif University of Technology ; Mousavi, Abbas (Supervisor) ; Bastani, Daruish (Supervisor)
Abstract
This study aims to investigate polysulfone (PSF) hollow fiber mixed matrix membranes (MMMs) properties containing Uio-66-NH2 and Mil-125-NH2 nanoparticles, groups of metal-organic frameworks (MOFs), for hemodialysis application. The nanoparticles were synthesized, and the membranes were produced by the phase inversion method. Membranes characterization conducted by ATR-FTIR, FE-SEM, EDX, TEM, and AFM was confirmed the presence of MOFs nanoparticles. Also, the evaluation of specific surface area of nanoparticles was done by BET. The water contact angle (WCA) results indicated the improvement of MMMs hydrophilicity, enhancing the pure water flux from 46.8 L/ m2h for the pristine membrane to...
Complex Activity Recognition by Means of an IMU-Based Wearable System for the Purpose of PD Patients’ Rehabilitation
, M.Sc. Thesis Sharif University of Technology ; Behzadipour, Saeed (Supervisor) ; Ali Beiglou, Leila (Co-Supervisor)
Abstract
Parkinson's is a disease caused by a disorder in the central nervous system of the body. There is no definite cure for this disease, but one of the ways to prevent the progress of this disease is to use movement therapy. One of the goals of designing wearable systems consisting of inertial sensors is to make it possible to perform this movement therapy from a distance. The purpose of the present study and research is to use the approach of simple and complex activities in order to increase the accuracy in the detection of activities and also to solve the problems of the previous system, with the help of creating the ability to detect complex meaningful activities for Parkinson's patients. In...
Robustness Improvement of the PD Patients' Activity Recognition Algorithm in Presence of Variations in Patients' Motion Patterns (Inter-Class Variations)
, M.Sc. Thesis Sharif University of Technology ; Behzadipour, Saeed (Supervisor)
Abstract
Parkinson’s disease is considered as a progressive neurodegenerative disease that hasn’t any certain treatment. In Iran until 1390, there were about 150 thousand patient struggling with this disease. Rehabilitation is known as an effective treatment to decrease destructive progress of the disease. Because of motional problems of PD patients, it is hard to come to the clinics. So developing remote rehabilitation would be interested by researchers and occupational therapists. Therefore in the recent years, an activity recognition system has been developed in Mowafaghian research center. This system is based on IMU sensors and a NM classifier.These systems are challenging with some problems,...
Intelligent Diagnosis of Cardiovascular Disease using ECG Signals
, M.Sc. Thesis Sharif University of Technology ; Haj Sadeghi, Khosrow (Supervisor)
Abstract
Cardiovascular diseases (CVDs) have ranked first cause of deaths globally. In 2016, about 17.7 million people died from CVDs representing 31% of all world deaths. So, early intelligent detection of cardiovascular disease could help to save many lives in worldwide. There are several methods to analyze heart activity and to detect any abnormalities including Electrocardiogram, Stress test, Echocardiography, cardiac catheterization and coronary angiography.Among all methods, Electrocardiogram (ECG) is the most common and convenient type where it measures heart electrical activity and records it as a series of pulses. Analyzing these pulses would provide useful information about normal and...
Investigation of Modeling Arterial Tissue Growth and Remodeling Under Biaxial Loading Conditions
, M.Sc. Thesis Sharif University of Technology ; Asghari, Mohsen (Supervisor)
Abstract
Cardiovascular diseases are one of the leading causes of death in the world. Identifying the mechanical behavior of arteries and their growth and remodeling under applied loadings can help to better understand the progression of the disease and provide more effective clinical interventions. Therefore, many researchers in recent decades have turned their attention to modeling the process of stress-mediated growth and remodeling in soft tissues. Among the most important models proposed to study this process are the constrained mixture model proposed by Humphrey et al. and the volumetric growth model proposed by Hoger et al.. The constrained mixture model is based on the continuous turnover of...
The Dynamic and the Geometry of Disease Outbreaks by Redefining the Effective Distance
, M.Sc. Thesis Sharif University of Technology ; Ghanbarnejad, Fakhteh (Supervisor)
Abstract
An infectious disease can spread through different communities via mobility networks. In this study we address three basic questions related to this matter in the meta-population approximation: firstly, where did the disease start? Secondly, when did the disease start? Thirdly, how does it spread in the network? To answer these questions, we introduce a generic mathematical framework with appropriate physical assumptions and study the spread of diseases. Then, with analytical solutions, we bring up different algorithms in order to answer these three questions. Using these algorithms, we redefine the effective distance and arriving time and unveil the simple geometry of the disease outbreak
Expansion Modeling of Coronary Stent for Selection of Optimized Stent
,
M.Sc. Thesis
Sharif University of Technology
;
Movahhedy, Mohammad Reza
(Supervisor)
Abstract
Referring to mortality increasment having sprung from atherosclerosis, work on treatment of coronary heart disease seems to be necessary. Stent implementation is one of stenosis treatment. Stent deployment has been done during past two decades, but clinical evidence showed that because of some weakness in designing and implementing, restenosis occurs again. Material, structure and coating texture of stent are the designing criteria beside stent implementation importance. Thus a lot of activities have been done in this area to improve performance of these applications. Nowadays a lot of companies' researchers try the best to get better their products; consequently there is different types of...
Design and Efficient Implementation of Deep Learning Algorithm for ECG Classification
, M.Sc. Thesis Sharif University of Technology ; Hashemi, Matin (Supervisor)
Abstract
Cardiovascular diseases are the leading cause of death globally so early diagnosis of them is important. Many researchers focused on this field. First signs of cardiac diseases appear in the electrocardiogram signal. This signal represents the electrical activity of the heart so it’s primarily used for the detection and classification of cardiac arrhythmias. Permanent monitoring of this signal is not possible for specialists so we should do this by means of Artificial Intelligence. In this thesis, we use recurrent neural networks to classify electrocardiogram’s arrhythmias. This deep learning method, use two sources of data to learn from. The first part of data is global for everyone and the...
Design, Fabrication and Analyses of an Ultrasonic Probe for Kidney Lithotripsy Device
, M.Sc. Thesis Sharif University of Technology ; Ahmadian, Mohammad Taghi (Supervisor) ; Firoozbakhsh, Keykhosrow (Supervisor)
Abstract
Kidney stone disease is one of the diseases that a large number of people experience each year.A Common method for the treatment of kidney stone is the use of acoustic waves, which have attracted the attention of doctors in recent decades. Because of the different structure of kidney stones, the waves transmitted to break these stones are usually performed at different frequencies. Most kidney stones are calcium that can be broken down by using acoustic wave frequencies in the range of 40-20 KHz. Most available lithotripters for the treatment of percutaneous nephrolithotomy (PCNL) are two types: Pneumatic and piezoelectric lithotripters. The lithotripter in this thesis is a piezoelectric...
Queue Modeling of Patients in Waiting list of Kidney Transplantation
, M.Sc. Thesis Sharif University of Technology ; Modarres Yazdi, Mohammad (Supervisor)
Abstract
As the number of patients waiting for receiving kidney transplantation increases all over the world, the average waiting time for a patient in queue rises too, and consequently, the rate of death goes beyond the accepted level. Also, unbalanced numbers of donors and patients with same blood type make the problem bolder. The aim of this research is to design a queuing model in which kidney could be transplanted from deceased donors to patients with different but compatible blood type (Cross-Transplantation) in order to make the average waiting time for patients with different blood type closer to each other. In other words, the transplant system is supposed to make a decision whether to...