Mohammad Sirousazar; Helga Zebardast; Zeinab Hosseini Dastgerdi; Farshad Kheiri
Volume 13, Issue 4 , December 2019, , Pages 349-360
Abstract
In this research, the response of a novel drug delivery system responsive to the temperature, as a unique stimulus, was studied. The performance of the system was modeled at the unsteady state, using the numerical method. The system has three individual layers, containing a drug core, a phase-transient ...
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In this research, the response of a novel drug delivery system responsive to the temperature, as a unique stimulus, was studied. The performance of the system was modeled at the unsteady state, using the numerical method. The system has three individual layers, containing a drug core, a phase-transient intermediate layer and an external protective layer. The system has the ability to start and stop the release of the drug, according to the On-Off mechanism, by exerting any changes in the temperature of the release medium. Mathematical modeling was performed by solving the heat and mass transfer equations governing the layers of the system at the unsteady state. The lag time of system at On state, the drug release kinetics at On state and undesired drug release kinetics at Off state were determined as functions of the parameters of the system. The results obtained from the modeling showed that response of the system was under the influence of different parameters, such as the geometry of the system, the kind of constituents of the intermediate and protective layers and the ratio of the thermal conductivity of the intermediate layer at molten state to the thermal conductivity of the protective layer. It was shown that a reduced lag time for the system could be achieved by manipulating these parameters. From the viewpoint of the drug release kinetics at On state, it could be declared that the amount of the released drug is a function of the time constant of the system and the drug release could be increased by decreasing the time constant value. The results also showed that the undesired release of the drug could be accelerated by adjusting the parameters of the protective layer, such as the kind of constituents and the thickness of the layer. Using the obtained results from the numerical modeling, one can design and produce the temperature-responsive smart drug delivery systems with desired characteristics for practical applications.
Bioinformatics / Biomedical Informatics / Medical Informatics / Health Informatics
Mina Jafari; Behnam Ghavami; Vahid Sattari Naeini
Volume 9, Issue 4 , February 2015, , Pages 375-386
Abstract
The inference of Gene Regulatory Network (GRN) using gene expression data is significantly important in order to understand gene dependencies, regulatory functions among genes, biological processes, way of process occurrence and avoiding some unplanned processes (disease). The accurate inference of GRN ...
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The inference of Gene Regulatory Network (GRN) using gene expression data is significantly important in order to understand gene dependencies, regulatory functions among genes, biological processes, way of process occurrence and avoiding some unplanned processes (disease). The accurate inference of GRN needs the accurate inference of predictor set. Generally, the main limitations of the predictor set inference are the small number of samples, the large number of genes and also the possibility influence of noise in gene expression data. Hence, providing efficient methods to infer predictor set with high reliability is a serious need. In this paper, an efficient method is proposed to infer predictor set using Gravitational Search Algorithm (GSA). A GSA is used for each target gene to infer the predictor subset of the gene. In a population, a mass represents a predictor subset of the associated gene. The initial population per target gene is generated by Pearson Correlation Coefficient (PCC). In order to guide the GSA, Mean Conditional Entropy (MCE) is used as the assessment criterion. Experimental results show that the proposed method has a good ability to infer the predictor set with high reliability. In addition, we also compared the proposed algorithm with a recent similar method based on genetic algorithm. Comparison results reveal the advantage of the proposed algorithm on biological datasets with small data volumes and large network scales.
Nanobiotechnology / Bionanotechnology / Nanobiology
Mah Monir Karimzade; Ladan Rashidi; Fariba Ganji; Mitra Ahmadi; Sattar Tahmasebi Enferadi
Volume 8, Issue 4 , February 2015, , Pages 385-398
Abstract
The aim of this research is the preparation of a system based on mesoporous silica nanoparticles (MSN) for delivery of Rivastigmine hydrogen tartrate and investigating of the system cytotoxicity, with or without drugs, on the human brain neuroblastoma cells (SY5Y). Rivastigmine is a hydrophilic and a ...
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The aim of this research is the preparation of a system based on mesoporous silica nanoparticles (MSN) for delivery of Rivastigmine hydrogen tartrate and investigating of the system cytotoxicity, with or without drugs, on the human brain neuroblastoma cells (SY5Y). Rivastigmine is a hydrophilic and a hydrophobic drug which is used for treatment of Alzimerʾs disease. In this study MSN were synthesized and characterized by scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, x-ray diffraction, N2 adsorption isotherms, and z-potential analysis. Results showed that all MSN were spherical with the same structure. The mean size of nanoparticles was 100±13 nm and the mean diameter of pores was 2.15 nm. The loading capacity and efficiency of rivastigmine hydrogen tartrate were obtained 20.88, and 25%, respectively. Release of rivastigmine from nanoparticles in the simulated gastric and body fluid during 24 h were obtained 70.5 and 79.6%, respectively, which was shown the slightly fast release of rivastigmine in simulated gastric fluid. The cytotoxicity effect of nanoparticles with and without rivastigmine was done by MTT assay on SY5Y cell lines. Results showed that the in vitro rivastigmine release from the nanoparticles containing of it exhibited the more treatment property as free rivastigmine on SY5Y.
Computational Biomechanics
Faeze Jahani; Malikeh Nabaei; Zhenxiang Jiang; Seungik Baek
Volume 16, Issue 4 , March 2023, , Pages 20-30
Abstract
An abdominal aortic aneurysm is a gradual enlargement of the diameter of the aorta, which can threaten the patient's life if it ruptures. Several factors are effective in reducing aneurysm rupture risk and behavior. One of the important factors is the geometric characteristics of the aneurysm. It is ...
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An abdominal aortic aneurysm is a gradual enlargement of the diameter of the aorta, which can threaten the patient's life if it ruptures. Several factors are effective in reducing aneurysm rupture risk and behavior. One of the important factors is the geometric characteristics of the aneurysm. It is necessary to examine the geometric characteristics (shape and maximum diameter) of abdominal aortic aneurysms for each patient to predict the risk of aneurysm rupture and its behavior. Growth and remodeling models based on the finite element method are tools for describing biological characteristics and predicting the progression of diseases such as abdominal aortic aneurysms. In this article, a stress-mediated growth and remodeling model was used to simulate different geometries of abdominal aortic aneurysms with the help of elastin damage function and collagen turnover. The simulation results emphasized the role of elastin damage on the geometrical changes of the aneurysm and the sensitivity of collagen turnover on wall stress distribution and expansion rate, so that with the change of the collagen rate from 0.07 to 0.04, the wall stress increased up to 300 kPa. The results showed that the stress distribution and local expansion correspond to the amount of elastin damage. The elastin damage function plays a key role in determining the location of the maximum diameter and in creating different forms of abdominal aortic aneurysms. Furthermore, time changes have a direct impact on elastin degradation. The remodeling of collagen, which was caused by increasing stress, compensated for the loss of elastin and controlled the expansion rate of the aneurysm. In the future, this computational model will have the ability to depict patient-specific abdominal aortic aneurysm growth with the help of the geometrical changes of the aneurysm, the amount of elastin damage, and collagen remodeling.
Rehabilitation Engineering
Nima Jamshidi; Mostafa Rostami; Siamak Najarian; Mohammad Bagher Menhaj; Mohammad Saadatnia; Firouz Salami
Volume 2, Issue 1 , June 2008, , Pages 57-64
Abstract
In this research the kinematics parameters derived from ground reaction forces were evaluated to limit the differential diagnoses and measure the degree of disabilities during the walking among neuropathic subjects. 25 neuropathic subjects affected by drop foot and 20 normal subjects were enrolled in ...
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In this research the kinematics parameters derived from ground reaction forces were evaluated to limit the differential diagnoses and measure the degree of disabilities during the walking among neuropathic subjects. 25 neuropathic subjects affected by drop foot and 20 normal subjects were enrolled in the study. There were no differences in the age, weight and height between the patients and normal subjects (p > 0.05). Each subject was tested in average 10±2 times for calculating the kinetic parameters derived from ground reaction forces. Then time parameters and vertical components of force including three extremums of vertical forces, which state various phases in gait, anterior-posterior component of ground reaction force, maximum propulsion force, maximum breaking force during loading stage, maximum propulsion force in the end phase of terminal stance, impact derived from the contact of the patient' foot with floor, loading rate and unloading of vertical forces during the contact' phase of the patient's foot with floor and center of pressure displacement in sole of foot and friction' coefficient between foot and floor were calculated. The results revealed that correlation between the first and second peaks of the anterior-posterior component of ground reaction forces, center of pressure displacement pattern in the sole of foot and time parameters of the vertical forces can be good indexes for differential diagnoses and measuring the degree of disabilities. This research can extend the clinical applications of ground reaction force plate, introduce suitable criteria to limit differential diagnoses and measure the degree of disabilities among the neuropathies. There is a need to replicate this research with more patients and normal subjects to confirm our findings.
Biomedical Image Processing / Medical Image Processing
Mohammad Mahdi Alimoradi; Mohammad Bagher Khodabakhshi; Shahriar Jamasb
Volume 17, Issue 1 , May 2023, , Pages 61-70
Abstract
Stroke is one of the causes of death and the main cause of disability in developed countries. Normally, identification of stroke lesions is done by magnetic imaging, and its analysis requires the continuous presence of a doctor in the treatment center. Therefore, intelligent processing of medical images ...
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Stroke is one of the causes of death and the main cause of disability in developed countries. Normally, identification of stroke lesions is done by magnetic imaging, and its analysis requires the continuous presence of a doctor in the treatment center. Therefore, intelligent processing of medical images will be an effective approach for automatic diagnosis of brain lesions.In this paper, a new integrated framework based on fuzzy inference system and deep neural network for automatic segmentation of brain lesions is introduced. In this regard, firstly, an improved U-net deep network (U-net) has been introduced for lesion detection and segmentation, which includes increasing the number of encoder and decoder layers along with changing the activation functions. Then, by using a fuzzy inference system based on if-then rules used by membership functions, the proposed approach of this study, which is based on the pre-processing of input images and the use of the unit network, has been introduced.The results showed that the integration of the fuzzy inference system in the pre-processing with the improved deep network could increase the DICE coefficient up to 0.84. In addition, improving the contrast of the input images by the fuzzy system compared to the usual pre-processing methods such as histogram equalization showed a much better performance in the detection of lesions with small dimensions, which is due to the ability to control the amount of contrast increase in the fuzzy systems compared to the usual methods.
Biological Computer Modeling / Biological Computer Simulation
Azade Ahouraei; Farzad Towhidkhah; Fateme Haji Ebrahim Tehrani; Rasoul Khayati
Volume 1, Issue 1 , June 2007, , Pages 63-69
Abstract
Jaundice (hyperbilirubinemia) is a common disease in newborn babies. Under certain circumstances, elevated bilirubin levels may have detrimental neurological effects. In some cases, phototherapy is needed to lower the level of total serum bilirubin, which indicates the presence and severity of jaundice. ...
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Jaundice (hyperbilirubinemia) is a common disease in newborn babies. Under certain circumstances, elevated bilirubin levels may have detrimental neurological effects. In some cases, phototherapy is needed to lower the level of total serum bilirubin, which indicates the presence and severity of jaundice. Recently, diagnosis and treatment modeling of disease have been considered by many researchers. In this paper, we present two models for classification and prediction of neonatal jaundice. The models are based on recorded data of Iranian Neonates. This study is oriented on the basis of following procedures: a short review on physiology of Jaundice, and then description of the models. Two three-layer feed forward neural networks were used in the modeling. The neural network model for classification is able to specify the type of jaundice, and the model for prediction can evaluate the risk of jaundice for newborns. These models can be used to decrease the risk in the critical cases as well as the cost of treatment.
Cardiovascular Biomechanics
Ahmad Ramezani Saadatabadi; Majid Ahmadlouy Darab; Farzan Ghalichi; Ataollah Kamyabi
Volume 4, Issue 1 , June 2010, , Pages 65-72
Abstract
This study aimed to simulate three dimensional pulsatile Newtonian blood flow in End-to-Side anastomosis of Aorta-coronary bypass using ascending aorta velocity flow wave as graft inlet and left anterior descending coronary artery (LAD) velocity flow wave as coronary inlet for 50% symmetric stenosis. ...
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This study aimed to simulate three dimensional pulsatile Newtonian blood flow in End-to-Side anastomosis of Aorta-coronary bypass using ascending aorta velocity flow wave as graft inlet and left anterior descending coronary artery (LAD) velocity flow wave as coronary inlet for 50% symmetric stenosis. We have supposed that LAD walls were rigid and had no spatial mobility due to heart beats. In order to investigate the graft angles effects on blood flow, especially on the wall shear stress magnitudes, 20, 30 and 40 degrees graft angles were used. Using ascending aorta and LAD pulses simultaneously as boundary conditions for the first time is one of the important features of this study because already these boundary conditions have not been used simultaneously. We considered prograde flow effects. Appearance of recirculation flows in various degrees of grafting angles, existence of secondary flows and increased in their effects specially in pulses deceleration phase, existence of double core helical flows and increase in their intensify specially at the systole peak and the rise in the spatial wall shear stress gradient by increasing in the graft angle are some of important results of this study. Finally, according to our assumptions we suggest 20 to 30 degrees as desired angles for grafting.
Fluid-Structure Interaction in Biological Media / FSI
Hamed Khalesi; Hanie Niroomand Oscuii; Farzan Ghalichi
Volume 5, Issue 1 , June 2011, , Pages 67-78
Abstract
Biomechanics believe that, the arteries are remodeled under the influence of hemodynamic and mechanical factors. Biomechanical factors such as Opening Angle and the Tethering could have important effects on this phenomenon. The effects of various Opening Angle and Tethering during thoracic aorta aging ...
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Biomechanics believe that, the arteries are remodeled under the influence of hemodynamic and mechanical factors. Biomechanical factors such as Opening Angle and the Tethering could have important effects on this phenomenon. The effects of various Opening Angle and Tethering during thoracic aorta aging on arterial wall stress have been studied. ADINA software is used for numerical simulation.In this study, for the first time, numerical methods of Fluid-Structure Interaction have been used to study and simulate effects of Opening Angle and the Tethering in elastic artery remodeling due to age. Large deformation theory has been used for modeling changes of arterial radius; furthermore, behavior of Newtonian fluid has been used for blood. Pulsatile pressure and physiological Pulsatile flow waveforms have been applied to simulate transient behavior of arterial system. The results show that opening angle has further effect on circumferential stress so smooth distribution of circumferential stress on the wall accrued. Also, increasing Opening Angle with age reverses the circumferential stress distribution slop across the arterial wall. Tethering has further effect on axial stress. Decreasing Tethering in remodeling process over age leads to increase stress levels in the aged artery. Also, arterial wall shear stress in remodeled artery shows significant reduction in maximum, mean and amplitude values that caused reduction of pathological effects of endothelial cells.
Biomedical Image Processing / Medical Image Processing
Nojtaba Hajihasani; Yaghoub Farjami; Bijan Vosoughi Vahdat; Jahangir Tavakoli
Volume 3, Issue 1 , June 2009, , Pages 67-77
Abstract
Increasing number of diagnostic and therapeutic applications of finite amplitude ultrasound in medicine and biology has motivated researchers toward more accurate modeling and more efficient simulation of nonlinear ultrasound regime. One of the most widely used nonlinear models for propagation of 3D ...
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Increasing number of diagnostic and therapeutic applications of finite amplitude ultrasound in medicine and biology has motivated researchers toward more accurate modeling and more efficient simulation of nonlinear ultrasound regime. One of the most widely used nonlinear models for propagation of 3D diffractive sound beams in dissipative media is the KZK (Khokhlov, Kuznetsov, Zabolotskaya) parabolic nonlinear wave equation. Various numerical algorithms have been developed to solve the KZK equation. Generally, these algorithms fall into one of the three main categories: frequency domain, time domain and combined time-frequency domain. The intrinsic parabolic approximation in the KZK equation imposes limiting accuracy in the solution to the diffraction term of the KZK equation particularly for field points close to the source or in far off-axis region. In this work we developed a novel generalized time domain numerical algorithm to solve the diffraction term of the KZK equation. The algorithm solves the Laplacian operator of the KZK equation in the 3D Cartesian coordinates using novel 5-point Implicit Backward Finite Difference (IBFD) and 5-point Crank-Nicolson Finite Difference (CNFD) techniques. This leads to a more uniform discretization of the Laplacian operator which in turn results in a more accurate solution to the diffraction term in the KZK equation. Comparison between results obtained with the new algorithm and the previously-published data for rectangular ultrasound sources is presented.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Alireza Rezaei; Sara Belbasi
Volume 10, Issue 1 , May 2016, , Pages 69-83
Abstract
In this paper, a hybrid algorithm has been developed by analyzing the audio signals of the heart, that consists of extracting features based on chaos technique, reducing dimensions and analyzing the main components and classifying outputs by relying on comparative neuro-fuzzy networks. Uncertainty and ...
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In this paper, a hybrid algorithm has been developed by analyzing the audio signals of the heart, that consists of extracting features based on chaos technique, reducing dimensions and analyzing the main components and classifying outputs by relying on comparative neuro-fuzzy networks. Uncertainty and high error in the diagnosis of inter-ventricular openings are one of the common problems with the previous methods. Due to the importance of the auto-diagnosis of this heart condition, it is necessary to be well-designed and far from error. Transmission of feature spaces to their mapping by the main component analysis algorithm is made by two steps, selecting the number of 18 to 25 attributes among about 50 extracted attributes that these informations are input of the class. The proposed classification classifies the adaptive fuzzy neural network system with the possibility of predicting the incidence of heart disease, which predicts the number of repetitions at the acceptable level of outputs by entering the data. The data are from the Umich database at the University of Michigan and include samples from the ventricular aperture. The ratio of data split in the learning and testing phase is from 0.9 to 0.1 (cross-check), and the K-fold validation method is used. Calculation of criteria such as accuracy, sensitivity and uncertainty by the concept of entropy in a hybrid algorithm suggests the proper performance of the proposed method.
Computational Neuroscience
Naser Sadeghnejad; Mehdi Ezoji; Reza Ebrahimpour
Volume 14, Issue 1 , May 2020, , Pages 69-79
Abstract
Object recognition is one of the main cognitive abilities of human and animals. Human visual system, as a fast and accurate system can be a source of inspiration for the computational models of object recognition. Studies on the human visual system have emphasized its processing over time, whereas it ...
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Object recognition is one of the main cognitive abilities of human and animals. Human visual system, as a fast and accurate system can be a source of inspiration for the computational models of object recognition. Studies on the human visual system have emphasized its processing over time, whereas it is not considered in the conventional computational models of object recognition. In this paper, we attempt to present a time-based multilevel model for object recognition. In the first layer of the model, the input image information is sent to the next layer in a temporal representation. In the middle layer of the model, a deep neural network is used as a feature extractor. Finally, in contrast to the popular computational models for object recognition, a decision-making model such as drift-diffusion model is proposed based on the neuronal decision-making mechanisms in the brain. In other words, adaption to the human visual system has been considered in all of three layers. Several experiments have been conducted to evaluate the performance of the proposed computational model in object recognition. The experimental results show that as the input image becomes more complicated, noise increases, or occlusion occurs, the performance/reaction time of the model decreases/increases, which is consistent with the behavior of human visual system. The performance of the model for object recognition and base-level categorization is also investigated for application of the original images and the inverted images. The results show the difference between the processes of the object recognition and base-level categorization, which is consistent with the behavior of human visual system reported in the referenced papers.
Fluid-Structure Interaction in Biological Media / FSI
Saeed Nahidi; Alireza Hossein-Nezhad; Nasser Fatouraee; Zahra Heidari
Volume 6, Issue 1 , June 2012, , Pages 71-79
Abstract
Hemodynamic parameters are always affected by stenosis severity of arterial and these parameters in their turn have influence on the development of atherosclerosis. In this paper, By considering three different stenosis severity, the effects of wall porosity assumption on the hemodynamic parameters of ...
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Hemodynamic parameters are always affected by stenosis severity of arterial and these parameters in their turn have influence on the development of atherosclerosis. In this paper, By considering three different stenosis severity, the effects of wall porosity assumption on the hemodynamic parameters of a stenosed artery with a two-layer flexible wall (intima-media, adventitia), in which inner layer (intima-media) assumed porous, is numerically investigated, using Porous Fluid Structure Interaction (PFSI) model. Blood is assumed as an incompressible non-Newtonian fluid with pulsatile flow condition. In this investigation, the results show that the permeability assumption has much influenced on the hemodynamic characteristics so that the comparison of the results using PFSI with those of a non-porous model show 6% decrease in shear stress, 30% increase in displacement and more than 72% increase in effective stress in the porous layer.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Nader Jafarnia Dabanloo; Ahmad Ayatollahi; Vahid Jouhari Majd; Desmond Mclernon
Volume -2, Issue 1 , July 2005, , Pages 71-80
Abstract
The generation of electrocardiogram (ECG) signals by using a mathematical model has recently been investigated. One of the applications of a dynamical model which can artificially produces an ECG signal is the easy assessment of diagnostic ECG signal processing devices. In addition, the model may be ...
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The generation of electrocardiogram (ECG) signals by using a mathematical model has recently been investigated. One of the applications of a dynamical model which can artificially produces an ECG signal is the easy assessment of diagnostic ECG signal processing devices. In addition, the model may be also used in compression and telemedicine applications. It is also required that the model has capability to produce both normal and abnormal ECG signals. In this study, it is introduced a new method using radial basis function neural networks in a dynamical model based on McSharry model, to produce artificially the ECG signals. This new method has the advantage of capability to simulate a wider class of physiological signals (both normal and abnormal), compared to McSharry model. The simulation results are presented for normal ECG and three abnormal ones. The accuracy of the model has evaluated by using the error functions. The average of this error for a period of 100 seconds using 20 neurons is less than 2.5 percent for the four modeled cases (one normal and three abnormal).
Gait Analysis
Afsaneh Yavari; Mostafa Rostami; Ali Esteki; Ali Tanbakoosaz; Mehdi Yousefi Azar Khanian
Volume 7, Issue 1 , June 2013, , Pages 75-84
Abstract
Most of the recent biomechanical researches have been focused on the stability of people with disabilities and a few researches have been done on the athletes with high balance skill.The methods of elite athletes in keeping the balance can state valuable information about balance strategies and effective ...
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Most of the recent biomechanical researches have been focused on the stability of people with disabilities and a few researches have been done on the athletes with high balance skill.The methods of elite athletes in keeping the balance can state valuable information about balance strategies and effective parameters on balance. In this study we calculate local dynamical stability of musculoskeletal systems during a hard balance motion. Eight non elite athletes and six elite athletes in Wushu participatedin this study. Kinematic parameters for quantitative assessment of postural fluctuations were recorded by VICON ® Motion Analysis System. Using Lyapunov stability theory, stability and preparation of athletes were evaluated and the best model in performing the balance motion was shown to the coaches. Results from this study showed that motion pattern and preparation of athletes are effective in the displacements of center of mass and center of pressure and finally the stability of athletes.
Biomechanics of Bone / Bone Biomechanics
Iman Zoljanahi Oskui
Volume 12, Issue 1 , June 2018, , Pages 75-84
Abstract
With the increase in lifespan there are many concerns related to ability of the hard tissues such as teeth to meet the physical demands over an extended period of function. The dentin has a special microstructural feature that governs its mechanical behavior, e.g., fracture mechanics: cylindrical tubules ...
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With the increase in lifespan there are many concerns related to ability of the hard tissues such as teeth to meet the physical demands over an extended period of function. The dentin has a special microstructural feature that governs its mechanical behavior, e.g., fracture mechanics: cylindrical tubules that are called dentin tubules. These tubules are gradually occluded in the elderly. The present study is aimed to investigate the effects of microstructure and its aging-related changes of the considered fiber-reinforced composite dentin on the fracture behavior and crack propagation trajectory, utilizing linear elastic fracture mechanics and finite element method. Obtained results indicate that the crack propagation path depends on geometrical microstructure of the dentin as well as respective mechanical properties and arrangement of dentin tubules. Also our results delineate that occlusion of dentinal tubule due to the aging plays a significant role at crack propagation trajectory and behaves as a barrier to crack growth.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Mohammad Davood Khalili; Vahid Abootalebi; Hamid Saeedi-Sourck
Volume 16, Issue 1 , May 2022, , Pages 75-94
Abstract
The human brain is one of the most complex and heterogeneous networks, and brain signals contain a lot of information, so researchers in this field are always looking for proper solutions to select meaningful features and reduce the dimension of this information appropriately to lead to better classification. ...
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The human brain is one of the most complex and heterogeneous networks, and brain signals contain a lot of information, so researchers in this field are always looking for proper solutions to select meaningful features and reduce the dimension of this information appropriately to lead to better classification. Two of the new tools for brain signal processing are Graph Signal Processing (GSP) and Meta-heuristic and Evolutionary methods. In this paper, a geometric structure and a mixed structure are considered for the brain graph and the weights of the edges in the mixed structure are calculated by a combination of two measures: geometric distance and correlation. To reduce the graph dimension, the weighted degree metric and a combination of the Kron reduction method and Graph Fourier Transform (KG) are used to properly preserve the information of all vertices of the graph into the selected vertices. Feature extraction is performed by Ledoit-Wolf shrinkage estimation and Tangent Space Mapping (TSM) method. For dimension reduction of extracted features, Principal Component Analysis (PCA) method and feature selection based on Differential Evolution (DE) are used. The selected features are given to several well-known machine learning classifiers. To evaluate the performance of the proposed method, dataset IVa from BCI Competition III has been used. The results show that the average classification accuracy of the proposed KG-PCA method with SVM-RBF and DT classifiers, in the structural graph and the functional-structural graph, is higher than the TSM-GFT method expressed in previous studies, and the DT classifier has achieved an average accuracy of 91.15±1.17. Also, according to the obtained results, the performance of the proposed KG-DE method has been better compared to KG-PCA and in the best case, the average accuracy of the SVM-RBF classifier is equal to 95.50±1.27.
Cell Biomechanics / Cell Mechanics / Mechanobiology
Farhad Tabatabaei Ghomshe; Ahmad Reza Arshi; Masoud Mahmoudian; Mahyar Janahmadi
Volume -1, Issue 1 , June 2004, , Pages 77-92
Abstract
Effective pharmacological analysis encompassing both the pharmacodynamics and the pharmacokinetics of the heart, dictates the necessity for responses made by the main channel receptors, to be appropriately modelled. This approach is of critical value when the pharmacological responses of the organ during ...
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Effective pharmacological analysis encompassing both the pharmacodynamics and the pharmacokinetics of the heart, dictates the necessity for responses made by the main channel receptors, to be appropriately modelled. This approach is of critical value when the pharmacological responses of the organ during pathological states are under investigation. To this effect, the electrochemical phenomenon in the heart was simulated using a specifically simplified three dimensional model based on the cellular physiological concepts. Various advanced models for different types of heart cells were combined to produce a three dimensional model capable of describing the electrophysiological, electrochemical and geometric characteristics of a heart in a non-pathological state. Various cell type models such as central and peripheral SA node, AV node, atrial myocyte, ventricular myocyte, and specialized cells for rapid conductance like purkinje fibres were included in the 3D model. The cellular architecture in the model follows the non-heterogeneity of the heart structure accompanied by gap junctions representing cellular interconnections. Here the transport of Na+, Ca++, K+ and CL- was primarily governed by such factors as electrical and chemical potential gradients along with other energetic mechanisms. The simplified heart geometry is introduced through 18 layers with 25 cells in each layer. Model equations were solved to simulate a one second using a 2.6 GHz Pentium IV PC. The simulation was performed utilizing MA TLAB programming language which provides effective visualization capabilities. The CEP model could be adopted as a preliminary basis towards individualizations in pharmacology and electrophysiology.
Neuro-Muscular Engineering
Amir Masoud Ahmadi; Sepideh Farakhor Seghinsara; Mohamad Reza Daliri; Vahid Shalchyan
Volume 11, Issue 1 , May 2017, , Pages 83-100
Abstract
The brain stimulation and its widespread use is one of the most important subjects in studies of neurophysiology. In brain electrical stimulation methods, following the surgery and electrode implantation, electrodes send electrical impulses to the specific targets in the brain. The use of this stimulation ...
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The brain stimulation and its widespread use is one of the most important subjects in studies of neurophysiology. In brain electrical stimulation methods, following the surgery and electrode implantation, electrodes send electrical impulses to the specific targets in the brain. The use of this stimulation method is provided therapeutic benefits for treatment chronic pain, essential tremor, Parkinson’s disease, major depression, and neurological movement disorder syndrome (dystonia). One area in which advancements have been recently made is in controlling the movement and navigation of animals in a specific pathway. It is important to identify brain targets in order to stimulate appropriate brain regions for all the applications listed above. An animal navigation system based on brain electrical stimulation is used to develop new behavioral models for the aim of creating a platform for interacting with the animal nervous system in the spatial learning task. In the context of animal navigation the electrical stimulation has been used either as creating virtual sensation for movement guidance or virtual reward for movement motivation. In this paper, different approaches and techniques of brain electrical stimulation for this application has been reviewed.
Medical Robotics / Bio-Robotics
Mojtaba Sharifi; Saeid Behzadipour; Hasan Salarieh; Farzam Farahmand
Volume 9, Issue 1 , April 2015, , Pages 85-98
Abstract
In this paper, a transparent bilateral controller is developed for the control of telesurgery systems that have physical interactions with soft tissue. In this control method, the parameters of a viscoelastic model of the soft tissue are estimated during its interaction with the slave robot using an ...
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In this paper, a transparent bilateral controller is developed for the control of telesurgery systems that have physical interactions with soft tissue. In this control method, the parameters of a viscoelastic model of the soft tissue are estimated during its interaction with the slave robot using an on-line identification method. These estimated parameters are used inanimpedance control of the master robot which is in contact with the surgeon. Also, the slave robot tracks the master robot position using a tracking controller. Accordingly, it is shown that the transparency of the teleoperation system is obtained by estimating and realizing the dynamic parameters of the tissue for the master robot and providing the position tracking performance for the slave robot. The stability, and the position and force tracking performances are proved using the Lyapunov theorem. Moreover, the effectiveness of the proposed transparent bilateral controller is investigated by simulations performed on a piece of beef (as the soft tissue) using a two DOF robot with nonlinear dynamics. The proposed control strategy can be used in telesurgery, telesonography and telerehabilitation systems in which the robot interacts with soft tissues.
Bioelectrics
Fatemeh Parastesh; Sajad Jafari; Hamed Azarnoush
Volume 13, Issue 1 , April 2019, , Pages 85-93
Abstract
Spiral wave is a particular spatiotemporal pattern, observed in a wide range of complex systems such as neuronal network. Appearance of these waves is related to the network structure as well as the dynamics of its blocks. In this paper, we propose a new modified Hindmarsh-Rose neuron model. The proposed ...
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Spiral wave is a particular spatiotemporal pattern, observed in a wide range of complex systems such as neuronal network. Appearance of these waves is related to the network structure as well as the dynamics of its blocks. In this paper, we propose a new modified Hindmarsh-Rose neuron model. The proposed model uses a hyperbolic memductance function as the monotonically differentiable magnetic flux. An external electromagnetic excitation is also considered in the model. Firstly, we study the dynamics of the proposed neuron model through bifurcation diagram and Lyapunov spectrum, in two cases of no excitation and periodic excitation. The bifurcation diagram shows the property of antimonotonicity, which has not been observed in the previous models. Then a square network is constructed and we investigate the spatiotemporal pattrens. By varying the parameters values, spiral waves are observed in specific ranges. The formation of these waves depends on the interaction of all parameters simultaneously.
Biomedical Image Processing / Medical Image Processing
Mohammad Reza Rezaeian; Gholam Ali Hossein-Zadeh; Hamid Soltanian Zadeh
Volume 8, Issue 1 , March 2014, , Pages 87-99
Abstract
Chemical exchange saturation transfer (CEST) is a new mechanism of contrast generation in magnetic resonance imaging (MRI) which differentiates molecule biomarkers via chemical shift. CEST MRI contrast mechanism is very complex and depends on radio frequency (RF) power and RF pulse shape. Two approaches ...
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Chemical exchange saturation transfer (CEST) is a new mechanism of contrast generation in magnetic resonance imaging (MRI) which differentiates molecule biomarkers via chemical shift. CEST MRI contrast mechanism is very complex and depends on radio frequency (RF) power and RF pulse shape. Two approaches have been used to saturate contrast agent (CA) protons: continuous wave CEST (CW-CEST) and pulsed CEST. To find the optimal RF pulse, numerical solution of Bloch-McConnell equations (BME) may be used. In this paperwe find the optimum values of RF pulse parameters that maximize the CEST contrast. Discrete pulses have lower specific absorption ratio (SAR) than CW RF pulses. However, since discretization is performed on continuous RF pulses, optimizing the continuous RF pulses leads to the optimization of discrete RF pulses. Therefore, in this paper, Rectangular, Gaussian and Fermi pulses are investigated as CW RF pulses. In this investigation, in addition to considering the SAR limitation, 60 dB approximation for the RF pulse amplitude is used. To compare the efficiency of pulses, their resultant flip angles (FA) are assumed equal. Efficiency of CW-CEST is investigated using two parameters, CEST ratio and SAR. According to these parametres, rectangular, Fermi and Gaussian RF pulses have the best performance respectively. Since implementation of rectangular RF is harder than Gaussian and Fermi RF pulses, Fermi and Gaussian RF pulses are desired. Our results suggest that it is possible to maximize CEST ratio by optimizing parameters of rectangular (with an amplitude of 5.7μT), Gaussian (σ about 0.7s) and Fermi (a-value about 0.3s) pulses. Results are verified by empirical formulation of CEST ratio.
Nanobiotechnology / Bionanotechnology / Nanobiology
Mohadese Shahriaripour; Sasan Asiaei
Volume 15, Issue 1 , May 2021, , Pages 87-97
Abstract
Cerium oxide nanoparticles have many applications in medicine. Particle size, shape and concentration of nanoceria are very important for biological applications and biocompatibility. The synthesis method of cerium oxide nanoparticles has an important role in determining nanoceria shape, particle size ...
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Cerium oxide nanoparticles have many applications in medicine. Particle size, shape and concentration of nanoceria are very important for biological applications and biocompatibility. The synthesis method of cerium oxide nanoparticles has an important role in determining nanoceria shape, particle size and concentration. In this project, the effective parameters in determining the concentration, size and size distribution, crystallinity and production of maximum cerium oxide produced from the reactants were simulated and tested. Since in different method, particle size control has become an important challenge, microfluidic chips were used to control particle size. Among the existing methods for nanoparticle synthesis, co-precipitation method was chosen because of its simplicity, cheapness and short time method compared with other methods. Cerium nitrate and sodium hydroxide were used as raw materials to synthesize cerium oxide nanoparticles. Simulations were performed in Comsol and then the results were used for experimental tests, comparison and validation. The nanoparticles were characterized for size and size distribution using x-ray diffraction. The results of this study showed that the use of microfluidic chips is an effective method for controling nanoparticle size. Increasing concentration of sodium hydroxide can complete reaction and have maximum efficiency and decreasing the reactives velocity can reduce the size dispersion, increases the crystallinity and particle size. The yellow precipitate produced, according to Scherer equation, contains cerium oxide nanoparticles with particle size of 1.16±0.1 nm and 85% of crystallinity.
Musculoskeletal Systems Modeling
Hossein Rostami Barooji; Abdolreza Ohadi; Farzad Towhidkhah
Volume 17, Issue 2 , September 2023, , Pages 120-130
Abstract
Despite the extensive progress in the field of biomechanics of human gait, a suitable gait model with the ability to simulate the control system of the human brain has not yet been presented, especially in 3D mode. The importance of the issue increases when the simulation of human walking is one of the ...
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Despite the extensive progress in the field of biomechanics of human gait, a suitable gait model with the ability to simulate the control system of the human brain has not yet been presented, especially in 3D mode. The importance of the issue increases when the simulation of human walking is one of the main requirements of designers of biomechanical equipment such as artificial organs, wearable robots and humanoid robots. Regarding the constraints and complexities of previous studies, in this research, a forward dynamic 3D model of gait based on sliding mode controller (SMC) is presented, which simulates the walking behavior of healthy individual on the ground in different movement phases. One of the strengths of this research is the comprehensive and analytical review of 3D rotation consequences of the joints coordinate systems, which is done with 11 DOF inverse dynamic model. Based on the obtained results, the SMC controller is well able to produce stable 3D human gait. Also, in 3D gait analysis, the Cardan rotation sequence is not suitable and YXZ order should be used. This outcome is a very useful result for 3D motion generation for human like walking pattern. The results of this study can be used in the design of humanoid robots, active and passive prostheses. Also, the presented model can simulate the walking of an amputee with a prosthesis and the role of the controller in the path, which is very important and beneficial in terms of rehabilitation.
Nano-Biomaterials
Babak Mostaghasi; Mohammad Hossein Fathi; Mahmoud Sheikh Zeinaddin; Sabihe Soleimanianzad
Volume 1, Issue 2 , June 2007, , Pages 137-146
Abstract
Hydroxyapatite (HA) is a well known candidate for many applications in dentistry and medicine such as bone replacement and regeneration and coatings for medical implants. Nano-crystalline HA exhibits improved mechanical properties and biocompatibility. To optimize the benefits of nano-sized precursors, ...
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Hydroxyapatite (HA) is a well known candidate for many applications in dentistry and medicine such as bone replacement and regeneration and coatings for medical implants. Nano-crystalline HA exhibits improved mechanical properties and biocompatibility. To optimize the benefits of nano-sized precursors, the particles must be of a uniform shape and size and have minimum degree of agglomeration. The aim of this study was to synthesize of nano-crystalline HA via the biomineralization route. For this purpose, an Iranian strain of Serratia (Serratia marcescens PTCC 1187) was utilized for the synthesis of nano-crystalline HA. The strain was cultivated. Then the pellet of S. marcescens PTCC 1187 was separated and exposed to Glycerol 2-phosphate and Calcium chloride. After 14 days of incubation at 37oC, the white precipitated material was separated. After drying and calcination at 600oC the powder was characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD) and fourier transform infrared spectroscopy (FTIR) techniques. The results showed that nano-structured HA powder was synthesized and the crystallinity of the powder was relatively high according to the standard. The particles of the powder were single crystal with the size of 25-30 nm. Moreover, the shape and size of the particles were relatively uniform and the agglomeration was lower comparing to the conventional methods. This powder could be used in the regeneration of bone defects, fabrication of medical, dental implants and also as a vector for pharmaceuticals and biological materials such as the genes.
