Sharif Digital Repository

Epilepsy is one of the diseases that affects the quality of life of epileptic patients. Epileptic patients lose control during epileptic seizures and are more likely to face problems. Designing and creating a seizure detection system can reduce casualties from epileptic attacks. In this study, we present an automatic method that reduces the artifact from the raw signals, and then classifies the seizure and non-seizure epochs. At all stages, it is assumed that no information is available about the patient and this detection is made only based on the information of other patients. The data from this study were recorded in Temple Hospital and the recording conditions were not controlled, so... 

The brain electrical signal (EEG) has been widely used in clinical and academic research, due to its ease of recording, non-invasiveness and precision. One of the applications can be emotion recognition from the brain's electrical signal. Generally, two types of parameters (Valence and Arousal) are used to determine the type of emotion, which, in turn, indicate "positive or negative" and "level of extroversion or excitement" for a specific emotion. The significance of emotion is determined by the effects of this phenomenon on daily tasks, especially in cases where the person is confronted with activities that require careful attention and concentration.In the emotion recognition problem,... 

Attention is one of the important aspects of brain cognitive activities, which has been widely discussed in psychology and neuroscience and is one of the main fields of research in the education field. The human sense of hearing is very complex, impactful and crucial in many processes such as learning. Human body always does several tasks and uses different senses simultaneously. For example, a student who listens to his/her teacher in the class, at the same time pays attention to the teacher, looks at a text or image, and sometimes writes a note.Using the electroencephalogram (EEG) signal for attention assessment and other cognitive activities is considered because of its facile recording,... 

Time perception is a concept that describes how a person interprets the duration of an event. Depending on the circumstances, people may feel that time passes quickly or slowly. So far, the understanding, comparison, and estimation of the time interval have been described using a simple model, a pacemaker accumulator, that is powerful in explaining behavioral and biological data. Also, the role of the frequency band, Contingent Negative Variation (CNV), and Event-Related Potential (ERP) components have been investigated in the passage of time and the perception of time duration. Still, the stimuli used in these studies were not melodic. Predicting is one of the main behaviors of the brain.... 

Depression is a type of mental disorder that is characterized by the continuous occurrence of bad moods in the affected person. Studies by the World Health Organization (WHO) show that depression is the second disease that threatens human life, and eight hundred thousand people die due to suicide every year. In order to reduce the damage caused by depression, it is necessary to have an accurate method for diagnosing depression and its rapid treatment, in which electroencephalogram (EEG) signals are considered as one of the best methods for diagnosing depression. Until now, various researches have been conducted to diagnose depression using electroencephalogram signals, most of which were... 

Water in oil emulsion usually forms during natural water encroachment or enhanced oil recovery processes due to the reaction between asphaltenic and naphthenic acid part of oil with brine in some heavy oil reservoirs. This results in major production challenges because of high w/o emulsion viscosity which leads to significant pressure drops. Therefore, it is essential to investigate the dominant mechanisms of w/o emulsion flow in porous media to overcome the production challenges. In the present study, w/o emulsion behavior is investigated through both static and dynamic tests. The w/o emulsion was prepared through mixing of a crude with brine using magnet stirrer. Emulsion stability... 

The use of brain signals in controlling devices and communication with the external environment has been very much considered recently. The Brain-Computer Interface (BCI) systems enable people to easily handle most of their daily physical activity using the brain signal, without any need for movement. One of the most common BCI systems is P300 speller. In this type of BCI systems, the user can spell words without the need for typing with hands. In these systems, the electrical potential of the user's brain signals is distorted by visual, auditory, or tactile stimuli from his/her normal state. An essential principle in these systems is to exploit appropriate feature extraction methods which... 

Among the most costly diseases that affect a person's quality of life throughout his or her life, mental disorders (excluding sleep disorders) affect up to 25 percent of people in any community. One of the most common types of these disorders in Iran is depressive disorder, which according to official statistics, 13% of Iranians have some symptoms of it. Until now, the diagnosis of this disease has been traditionally done in clinics with interviews and questionnaires tests based on behavioral psychology and using symptom assessment. Therefore, there is a relatively low accuracy in the treatment process. Nowadays, with the help of functional brain imaging such as electroencephalogram (EEG)... 

Nowadays, Electroencephalogram (EEG) is the most common method for brain activity measurement. Event Related Potentials (ERP) which are recorded through EEG, have many applications. Detecting ERP signals is an important task since their amplitudes are quite small compared to the background EEG. The usual way to address this problem is to repeat the process of EEG recording several times and use the average signal. Though averaging can be helpful, there is a need for more complicated filtering. Blind source separation methods are frequently used for ERP denoising. These methods don’t use prior information for extracting sources and their use is limited to 2D problems only. To address these... 

The auditory system with its unique features has been considered by researchers in the past and its various parts from the outside of the body to its internal parts have been studied. The auditory nervous system, as the most important part of the auditory system, is responsible for receiving and processing information from the ear. The auditory system has different anatomical and physiological characteristics. The result of these characteristics is processing power in the field of time and frequency, which has received more attention in this dissertation. This processing power is most evident in the central auditory nervous system. This section includes nerve neurons and synapses from the... 

The Brain Computer Interface (BCI) translates brain signals into a series of commands, enabling individuals to fulfill many of their basic needs without physical activity. Electroencephalogram (EEG) signals are commonly used as input for BCI systems, because the recording of this signal is non-invasive, inexpensive, and also have an acceptable time resolution. One of the most prevalent methods in BCI systems is the brain-computer interface based on Steady State Visual Evoked Potentials (SSVEP). These systems provide high response speed and Information Transfer Rate (ITR) as well as a good signal-to-noise ratio (SNR). The main purpose of these systems is to detect the frequency of SSVEP in... 

The processing of brain signals, including the electrocorticogram (ECoG) signal, is widely used in the investigation of neurological diseases. Conventionally, the ECoG signal has frequency components up to the range of 80 Hz. Studies have proven that in some conditions, such as epilepsy, the brain signal includes frequency components higher than 80 Hz, which are called high-frequency oscillations (HFO). Therefore, HFOs are recognized as a biomarker for epilepsy. The aim of this thesis is to review the previous methods of detecting HFOs and to present new methods with greater efficiency in the direction of diagnosis or treatment of epileptic patients. For this purpose, we used the ECoG data... 

The Oil wells are usually damaged because of the drilling process and production scenarios or fluid injection during EOR processes. These damages would critically affect the rate of production and injectivity of the well in the form of plugging damage. Different methods are used to fix these damages and increase the production flow from the oil wells. One of the most widely used well-stimulation methods to remediate this challenge is well acidizing. Although this method has very high efficiency in improving the ability of wells, if it is not designed and implemented correctly and optimally, it can cause induced damage and even lead to the well shutting. This challenge is especially reported... 

In most of brain studies, the primary objective is to find dipole activities, an underdetermined problem that requires additional constraints. Adequate constraints can be added by using information from other modalities. This research aims to develop a platform that combines various noninvasive modalities to improve localization accuracy. To accomplish this, two novel general approaches to combining modalities are proposed. In the first approach, the result of localizing by different methods and in different modalities are processed and combined in intervals by Dempster Shaffer's combination law. The final amount of bipolar activity is obtained by cumulating the activities obtained at... 

EEG brain signals have gained particular attention among researchers in the field of brain signal processing due to their easy and cheap recording, high temporal resolution, and non-invasiveness. On the other hand, defects such as high vulnerability to various types of noise and artifacts have caused the main challenge before processing them to improve the signal-to-noise ratio and the interpretability of brain connectivity obtained from them. In order to solve these challenges, two important problems of "separation of desired and undesired signal subspace" and "functional and effective connectivity analysis" have been raised, respectively. In solving both problems, EEG signals are usually...