Sharif Digital Repository

Automatic detection of epileptic seizures can serve as a valuable clinical tool which involves a more objective and computationally efficient method for the analysis of EEG data in order to generate increasingly accurate and reliable results. Automatic seizure detection is also an important component of closed-loop responsive cortical stimulation systems. The goal of this study is to evaluate EEG-based features recently proposed for seizure detection to discover the optimum ones for a reliable seizure detection system. We extracted seizure detection features from intracranial EEG signals that were recorded during invasive pre-surgical epilepsy monitoring of people with drug resistant focal... 

This paper presents a method for ECG characteristic points detection based on Wavelet Transform (WT). Wavelet Transform leads to more accurate results in analyzing nonstationary signals such as ECG. The selected wavelet is quadratic spline wavelet. Using quadratic spline mother wavelet, a method for detection of QRS complex and T and P waves is presented and evaluated with the help of MIT-BIH Arrhythmia database. Experimental results show excellent performance of the proposed method. © 2009 IEEE  

This paper presents a methodology to extract a number of quantifier features to characterize volumetric behavior of trajectories in phase space. These features quantify expanding and contracting behaviors and complexity that can be used in nonlinear and chaotic signals classification or clustering problems. One of the features is directly extracted from the distance matrix and seven features are extracted from a matrix that is subsequently obtained from the distance matrix. To illustrate the proposed quantifiers, Mackey–Glass time series and Lorenz system were employed and feature evaluation was performed. It is shown that the proposed quantifier features are robust to different... 

Common similarity measures of time domain signals such as cross-correlation and Symbolic Aggregate approximation (SAX) are not appropriate for nonlinear signal analysis. This is because of the high sensitivity of nonlinear systems to initial points. Therefore, a similarity measure for nonlinear signal analysis must be invariant to initial points and quantify the similarity by considering the main dynamics of signals. The statistical behavior of local extrema (SBLE) method was previously proposed to address this problem. The SBLE similarity index uses quantized amplitudes of local extrema to quantify the dynamical similarity of signals by considering patterns of sequential local extrema. By... 

Blind source separation is an important field of study in signal processing, in which the goal is to estimate source signals by having mixed observations. There are some conventional methods in this field that aim to estimate source signals by considering certain assumptions on sources. One of the most popular assumptions is the non-Gaussianity of sources which is the basis of many popular blind source separation methods. These methods may fail to estimate sources when the distribution of two or more sources is Gaussian. Hence, this study aims to introduce a new approach in blind source separation for nonlinear and chaotic signals by using a dynamical similarity measure and relaxing... 

This study presents applying recurrence quantification analysis (RQA) on EEG recordings and their subbands: delta, theta, alpha, beta, and gamma for epileptic seizure detection. RQA is adopted since it does not require assumptions about stationarity, length of signal, and noise. The decomposition of the original EEG into its five constituent subbands helps better identification of the dynamical system of EEG signal. This leads to better classification of the database into three groups: Healthy subjects, epileptic subjects during a seizure-free interval (Interictal) and epileptic subjects during a seizure course (Ictal). The proposed algorithm is applied to an epileptic EEG dataset provided... 

Seizures are defined as manifest of excessive and hypersynchronous activity of neurons in the cerebral cortex and represent a frequent malfunction of the human central nervous system. Therefore, the search for precursors and predictors of a seizure is of utmost clinical relevance and may even guide us to a deep understanding of the seizure generating mechanisms. In this study we analyzed invasive electroencephalogram (EEG) recordings in rats with experimentally induced generalized epilepsy with a nonlinear method called, dissimilarity index. In order to predict epileptic seizures automatically, Bhattacharyya distance between trajectory matrix of reference window, during an interval quite... 

Epileptic seizures are generated by an abnormal synchronization of neurons. Since epileptic seizures are unforeseeable for the patients, epileptic seizures detection is an interesting issue in epileptology, that novel approaches to understand the mechanism of epileptic seizures. In this study we analyzed invasive electroencephalogram (EEG) recordings in patients suffering from medically intractable focal epilepsy with a nonlinear method called, dissimilarity index. In order to detect epileptic seizures Bhattacharyya distance between trajectory matrix of reference window during an interval quite distant in time from any seizure and trajectory matrix of present window is employed to measure... 

Objective: Epileptic seizures are defined as manifest of excessive and hyper-synchronous activity of neurons in the cerebral cortex that cause frequent malfunction of the human central nervous system. Therefore, finding precursors and predictors of epileptic seizure is of utmost clinical relevance to reduce the epileptic seizure induced nervous system malfunction consequences. Researchers for this purpose may even guide us to a deep understanding of the seizure generating mechanisms. The goal of this paper is to predict epileptic seizures in epileptic rats. Methods: Seizures were induced in rats using pentylenetetrazole (PTZ) model. EEG signals in interictal, preictal, ictal and postictal... 

Objective: Epileptic seizure detection is a key step for epilepsy assessment. In this work, using the pentylenetetrazole (PTZ) model, seizures were induced in rats, and ECoG signals in interictal, preictal, ictal, and postictal periods were recorded. The recorded ECoG signals were then analyzed to detect epileptic seizures in the epileptic rats. Methods: Two different approaches were considered in this work: thresholding and classification. In the thresholding approach, a feature is calculated in consecutive windows, and the resulted index is tracked over time and compared with a threshold. The moment the index crosses the threshold is considered as the moment of seizure onset. In the... 

Four 5-, 10-, 20- and 30-story moment frames, representing low-, mid-, and two high-rise structures, were subjected to a great number of idealized directivity pulses. The amplitudes and periods of pulses vary from 0.02 g to 1.0 g and 0.5 to 12 sec, respectively. Over 1400 nonlinear dynamic analyses of low- to high-rise moment frames were performed which were feasible through using modified fish-bone model. The distribution of interstory drift along the height was studied and two applied contours were proposed: (i) the maximum interstory drift contour, and (ii) the critical story contour. These contours were demonstrated versus the ratio of natural period of the structure to the pulse period... 

In this article singular points of a parallel manipulator are obtained based on a novel geometrical method. Here we introduce the constrained plain method (CPM) and some of its application in parallel mechanism. Given the definition of constraint plane (CP) and infinite constraint plane (ICP) the dependency conditions of constraints is achieved with the use of a new theorem based on the Ceva geometrical theorem. The direction of angular velocity of a body is achieved by having three ICPs with the use of another theorem. Finally, with the use of the above two novel theorems singularities of the 3UPF_PU mechanism are obtained. It should be emphasized that this method is completely geometrical,... 

An analytical model is proposed to study the effect of particle size on melting enthalpy and entropy of metallic nanoparticles (NPs). The Mott's and Regel's equations for melting entropy in the combination of core average coordination number (CAC) and surface average coordination number (SAC) of freestanding NPs are considered. Clusters of icosahedral (IC), body centered cubic (BCC), and body centered tetragonal (BCT) structure without any vacancies and defects are modeled. Using the variable coordination number made this model to be in good agreement with experimental and molecular dynamic (MD) results of different crystal structures. The model predicts melting entropy and enthalpy of... 

Grinding is widely used for manufacturing of components that require fine surface finish and good dimensional accuracy. In this study a thermo-mechanical finite element analysis is conducted to find out how grinding parameters can affect temperature and residual stress distribution in the workpiece. Results of parametric study presented in this work indicate, by carefully selecting the grinding parameters, minimum thermal and mechanical damage can be achieved. Higher workpiece velocities produce higher surface residual stress. By increasing depths of cut, depth of tensile residual stresses increases. Convection heat coefficient does not have any considerable effect on surface residual stress... 

Adaptive Noise Cancellation (ANC) is a well-known technique for background noise reduction in automobile and vehicular environments. The noise fields in automobile and other vehicle interior obey the diffuse noise field model closely. On the other hand, the ANC does not provide sufficient noise reduction in the diffuse noise fields. In this paper, a new multistage post-filter is designed for ANC as a solution to diffuse noise conditions. The designed post-filter is a single channel Linear Prediction (LP) based speech enhancement system. The LP is performed by an adaptive lattice filter and attempts to extract speech components by using intermediate ANC signals. The post-filter has no... 

Self-Compacting Concrete (SCC) is a unique type of concrete that can flow and fill spaces without the need for vibrating compaction, resulting in a dense and uniform material. This article focuses on estimating the compressive strength of SCC utilizing Artificial Neural Networks. Specifically, the study employs multilayer perceptrons with back-propagation learning algorithms, which are commonly used in various problem-solving scenarios. The study covers essential components such as structure, algorithm, data preprocessing, over-fitting prevention, and sensitivity analysis in MLPs. The input variables considered in the research include water, fine aggregate, super-plasticizer, fly ash, coarse... 

Seismic retrofits can significantly reduce the vulnerability of masonry buildings. Multiple seismic retrofit alternatives are often available for a given building. Estimating the cost of each candidate action is essential to selecting and implementing the appropriate seismic retrofit initiatives. This research harnesses the capabilities of various regression models for cost estimation. A dataset from 167 retrofit projects for masonry school buildings was used to develop models. Three main retrofit actions were taken into consideration: shotcrete, steel belt and fiber-reinforced polymer. Various regression methods, including multiple linear regression, ridge regression, lasso regression, and... 

Shot peening is widely used to improve the fretting fatigue strength of critical surfaces. Fretting fatigue occurs in contacting parts that are subjected to fluctuating loads and sliding movements at the same time. This paper presents a sequential finite element simulation to investigate the shot peening effects on normal stress, shear stress, bulk stress and slip amplitude, which are considered to be the controlling parameters of fretting damage. The results demonstrated that among the modifications related to shot peening, compressive residual stress has a dominant effect on the fretting parameters  

One-dimensional (1D) MgO structures were successfully synthesized via carbothermic reduction of mechanically activated mixture of MgO and graphite. Mechanical activation of source materials before carbothermic reduction can substantially enhance the formation of MgO products at a temperature (1000 °C) relatively lower than that required in previous approaches (≥1200 °C). However, the morphology of MgO formed is dependent on the degree of mechanical activation and the condition of the subsequent carbothermic reduction. Two distinctive morphologies were found for MgO products synthesized using our method: single crystalline nanorods with rectangular cross-sections whose diameters range from 50...