Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Mahdi Khezri; Seyed Mohammad Firoozabadi; Seyed Ahmad Reza Sharafat
Volume 8, Issue 4 , February 2015, , Pages 339-358
Abstract
In this study, we propose decision level fusion of multimodal physiological signals to design an affect identification system using the MIT database. Four types of physiological signals, including blood volume pressure (BVP), respiration rate (RSP), skin conductance and facial muscles activities (fEMG) ...
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In this study, we propose decision level fusion of multimodal physiological signals to design an affect identification system using the MIT database. Four types of physiological signals, including blood volume pressure (BVP), respiration rate (RSP), skin conductance and facial muscles activities (fEMG) were utilized as affective modalities. To collect the above-mentioned database, researchers used personalized imagery to elicit the desired affective states from a single subject and recorded the corresponding physiological signals simultaneously. In this study, the best subset of features for each signal was determined using previously calculated time and frequency domain features. To this end, sequential floating forward selection (SFFS) and RELIEF feature selection algorithms were evaluated. A new feature set, formed by concatenating the selected features, was partitioned into three subsets. Each subset was then fed into a classifier to identify the desired affective states. The majority voting method was applied to fuse the results obtained by the subsystems. Three types of classification methods, namely SVM, LDA and KNN were evaluated to design an affect identification system. The results showed remarkable performance from the system in identifying the desired scenarios with an acceptable accuracy and speed of response. Using the RELIEF feature selection method, along with SVM as a classifier, an overall recognition accuracy of 93.8% was obtained, which is better than the results reported with the use of the above-mentioned database so far.
Biomedical Image Processing / Medical Image Processing
Sharare Kian-Bostanabad; Mahmoud Reza Azghani; Leila Rahnama
Volume 9, Issue 4 , February 2015, , Pages 341-350
Abstract
The cervical multifidus muscle is known as one of the deep neck extensor muscles that its dysfunction have been reported in people with neck pain.With regard to the limits on the evaluation of this muscle activity using electromyography, ultrasound was used to find out its function recently. The aim ...
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The cervical multifidus muscle is known as one of the deep neck extensor muscles that its dysfunction have been reported in people with neck pain.With regard to the limits on the evaluation of this muscle activity using electromyography, ultrasound was used to find out its function recently. The aim of this study is evaluation of this muscle dimansions change during six shoulder joint activities in healthy subjects and people with chronic neck pain and providing predictive models. So The relationship between strength of shoulder joint during contraction with the changes of anterior-posterior dimension, lateral dimension, shape ratio and size of the cervical multifidus muscle were assessed using of Response Surface Method in the first step for subjects and activities and then for activities with subject blocking. Finally, predictive models were provided for abduction activity in 0-50% of maximum voluntary contraction (MVC) for healthy subjects and 50-100% for patients with data clustering. The anterior-posterior dimension showed a higher correlation with the shoulder joint strength than other factors. R2 values for this dimension in healthy subjects before and after data clustering is 0.552 and 0.66 and in patients is 0.339 and 0.505 respectively. Given the models correlation coefficient and its enhance by data clustering, it seems that evaluation of anterior-posterior dimension of this muscle during isometric abduction activiy of shoulder joint with the sttrength of 0-50% MVC for healthy subjects and 50-100% for patients with neck pain can be provide useful information about its function.
Fluid-Structure Interaction in Biological Media / FSI
Bahman Vahidi; Nasser Fatouraee; Ali Imanparast
Volume 2, Issue 1 , June 2008, , Pages 29-37
Abstract
Ureter reflux is one of the prevalent factors that causes pyelonefrit and sistit syndromes. Dilatation of ureter, renal pelves and calyx are detectable with reflux. In this paper, in order to analyze this phenomenon, an axisymmetric model was introduced. We utilized a rigid body, which is in contact ...
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Ureter reflux is one of the prevalent factors that causes pyelonefrit and sistit syndromes. Dilatation of ureter, renal pelves and calyx are detectable with reflux. In this paper, in order to analyze this phenomenon, an axisymmetric model was introduced. We utilized a rigid body, which is in contact with the outer ureter wall to model ureter contraction. The Navier-Stokes equations are solved for the fluid and a linear elastic model is used for ureter wall structure. The finite element equations for both the structure and the fluid were solved by the Newton-Raphson iterative method. The effect of ureter wall elasticity, pressure difference between the ureter inlet and outlet and the effect of the average velocity of peristaltic wave along the length of the ureter on the ureter outlet flow rate were analyzed. Moreover, the effect of the number of contraction waves on the pressure and flow relations in the ureter was analyzed. Increase in the number of contraction waves reduced the flow passing through the ureter. The results of investigating about the contraction wave velocity variations indicated that if average velocity the contraction wave was lower than a limited magnitude, its existence did not have any considerable effect on the ureter outlet flow rate. Finally improper function of urinary tubes junctions results in the passage of a part of back flow even in the case of low velocity beginning of the contraction wave.
Biomedical Image Processing / Medical Image Processing
Seyed Mohammad Shams; Gholam Ali Hossein-Zadeh; Mohammad Mehdi Karimi
Volume 1, Issue 1 , June 2007, , Pages 29-37
Abstract
In order to analyze the functional Magnetic Resonance Imaging (fMRI) data, the parameters of a nonlinear model for the hemodynamic system, so called Balloon model, were characterized and estimated. Two different approaches were applied to estimate these parameters. In the first step of both approaches, ...
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In order to analyze the functional Magnetic Resonance Imaging (fMRI) data, the parameters of a nonlinear model for the hemodynamic system, so called Balloon model, were characterized and estimated. Two different approaches were applied to estimate these parameters. In the first step of both approaches, the voxels which show neural activity were identified. Then, the parameters of the balloon model for these active voxels were estimated by both steepest descent algorithm, and through genetic algorithm. Proposed approaches were applied on experimental fMRI data and the parameters of nonlinear Balloon model were estimated for different brain voxels. Accuracy of these characterizations was assessed via comparing the measured time series at each voxel with the modeled time series. Also, it was shown that the results of the parameter-estimation are consistent with the results obtained from system characterization via Volterra Kernels (which were reported in previous studies). It was concluded that the suggested approaches could accomplish a nonlinear system characterization through numerical methods, whereas they avoid theoretical complexities and they have acceptable speed (especially steepest descent algorithm).
Biomedical Image Processing / Medical Image Processing
Amirhossein Chalechale; Ali Khadem
Volume 14, Issue 1 , May 2020, , Pages 31-42
Abstract
The well-timed and correct diagnosis of Bipolar Disorder (BD) followed by proper treatment is vital for avoiding the progress of the illness. Although using resting-state functional magnetic resonance imaging (rs-fMRI) data and the features extracted from them may have an important role in diagnosing ...
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The well-timed and correct diagnosis of Bipolar Disorder (BD) followed by proper treatment is vital for avoiding the progress of the illness. Although using resting-state functional magnetic resonance imaging (rs-fMRI) data and the features extracted from them may have an important role in diagnosing this kind of brain disorder, few researches have been conducted on this illness and the obtained results are not accurate. In this research we used a new approach to diagnose BD I. By using seed-based correlation we used the following 4 regions of interest in order to extract the connectivity maps for each subject: the posterior cingulate cortex (PCC) to probe the default mode network (DMN), the amygdala and the subgenual cingulate cortex (sgACC) to probe the salience network (SN) and the dorsolateral prefrontal cortex (dlPFC) to probe the frontoparietal network (FPN). After computing the connectivity maps for each subject we extracted the most important connectivities using different threshold on the t-value from the t-test that we applied on them and then we used a support vector machine (SVM) using only four combined features and a leave one out cross-validation (LOOCV) method to classify the two groups. The proposed method was done on rs-fMRI data from 49 healthy control subjects and 34 BD I patients and an accuracy of higher than 90% was obtained in differentiating the two groups from each other. Also there were no hyper-connectivity between the 4 ROIs and the rest of the brain regions for the BD I groups in relation with the healthy controls. The regions that had most of the hypo-connectivity with the 4 ROI’s that we used were: the angular gyrus (Ag) and the orbitofrontal cortex (OFC) with the PCC, the anterior cingulate cortex with the amygdala and the dlPFC and the inferior temporal gyrus (ITG) with the sgACC.
Biological Systems Modeling
Arman Marzban; Elham Amini Boroujeni
Volume 16, Issue 4 , March 2023, , Pages 31-40
Abstract
Considering that mathematical modeling is helpful in describing and analyzing the behavior of epidemic diseases. On the other hand, the accuracy and degree of freedom in modeling fractional order systems are more than that of integer order systems due to the presence of long-term memory property. This ...
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Considering that mathematical modeling is helpful in describing and analyzing the behavior of epidemic diseases. On the other hand, the accuracy and degree of freedom in modeling fractional order systems are more than that of integer order systems due to the presence of long-term memory property. This paper extends the existing integer order model of Covid-19 disease to fractional order systems using fractional order calculations.The proposed model’s positivity and bounded answers are proved using the invariant region theorem. Using the fixed point theory in Banach space, the existence and uniqueness of the solution of the proposed fractional order model are proved. The behavior of both integer and fractional order has been simulated and evaluated using real information published for Covid-19 in Thailand. The higher efficiency and accuracy of the proposed model of fractional order are confirmed in the simulation results.keywords: Covid-19, Fractional order Calculus, Mathematical modeling, The existence and uniqueness of the answer
Biomechanics of Bone / Bone Biomechanics
Behnoud Haghighi; Masoud Tahani; Gholam Reza Rouhi
Volume 5, Issue 1 , June 2011, , Pages 33-44
Abstract
Orthopedic screws are widely used devices for fixation of bone fractures. Progressive loosening of bone fixation screws, induced by stress shielding and subsequent adaptive bone remodeling, results in bone loss around the screw. A set of two-dimensional finite element models including cortical and cancellous ...
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Orthopedic screws are widely used devices for fixation of bone fractures. Progressive loosening of bone fixation screws, induced by stress shielding and subsequent adaptive bone remodeling, results in bone loss around the screw. A set of two-dimensional finite element models including cortical and cancellous bone with a functionally graded Ti-Hap screw was developed. A dimensionless set of stress-transfer parameters (STP) and strain energy density-transfer parameter (SEDTP) were developed to quantify the screw–bone load sharing. Lower STP and SEDTP values indicate weak stress and strain energy density transfer to bone which is a sign of stress shielding. The results indicated that STP and SEDTP values for FGM screw are higher than those of a fully metal screw. Moreover, reducing elastic modulus of metal fraction and increasing the volume fraction of ceramic decrease the stress shielding. For a partially graded screw (with both homogenous and FGM parts), the longer FGM part is, the greater are STP and SEDTP values. Furthermore, the results showed that decreasing compositional distribution exponent which shows composition change of FGM content from metal fraction toward ceramic fraction, increases the parameters. Results from this study are in admissible agreement with available clinical and experimental study.
Biomimetics
Saeed Rashidi; Seyed Mohammad Reza Hashemi Golpayegani; Ali Fallah; Farzad Towhidkhah
Volume 4, Issue 1 , June 2010, , Pages 33-44
Abstract
In drawing movements, the constraints imposed on the trajectory geometry properties and kinematics are known with two laws: 2/3 power law and isochrony phenomenon. In this paper experiments have been designed to study the relation between two empirical laws in straight and curved patterns of drawing ...
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In drawing movements, the constraints imposed on the trajectory geometry properties and kinematics are known with two laws: 2/3 power law and isochrony phenomenon. In this paper experiments have been designed to study the relation between two empirical laws in straight and curved patterns of drawing movements in 16-18 years old subjects. Providing two models of power is indicated that in drawing movements, invariant features can be defining. These features are independent of subject, direction and size of trajectory and together they can simplify the role of the upper motor control system and decrease the degrees of freedom and the computational complexity.
Biomedical Image Processing / Medical Image Processing
Babak Mohammadzadeh Asl; Ali Mahloojifar
Volume 3, Issue 1 , June 2009, , Pages 33-46
Abstract
In recent years, adaptive beam forming methods have been successfully applied to medical ultrasound imaging, resulting in significant improvement in image quality compared to non-adaptive beam formers. This improvement results from the fact that their weights are chosen based on the priori knowledge ...
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In recent years, adaptive beam forming methods have been successfully applied to medical ultrasound imaging, resulting in significant improvement in image quality compared to non-adaptive beam formers. This improvement results from the fact that their weights are chosen based on the priori knowledge of the received data and updated using current statistics of the array signal. Most of the adaptive beam formers presented in the ultrasound imaging literature are based on the minimum variance (MV) beam former, which can improve the imaging resolution while retaining the contrast. It is desirable that the beam former could improve the resolution and contrast, at the same time. To this end, in this paper, we have used temporal averaging besides the conventional spatial averaging to estimate the more accurate covariance matrix. Moreover, we have used the coherence factor weighting combined with MV beam forming to enhance the focusing quality and hence reducing the undesired side lobes. The efficacy of the proposed adaptive beam forming approach is demonstrated via a number of simulated and experimental examples.
Bioelectrics
Amin Mohammadian; Akram Ghorbali; Maryam Asadolah Tooyserkani; Razieh kaveh; kian Shahi
Volume 16, Issue 1 , May 2022, , Pages 33-50
Abstract
The interview analyst’s need to detect deception is a topic that has provided the conditions for providing solutions to empower them. So that, the experts and interview analysts can be assisted by automatically monitoring the subject's unsalient, unknown, or counterintuitive activities during the ...
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The interview analyst’s need to detect deception is a topic that has provided the conditions for providing solutions to empower them. So that, the experts and interview analysts can be assisted by automatically monitoring the subject's unsalient, unknown, or counterintuitive activities during the interview. The aim of this study was to combine quantitative and qualitative information to help improve the detection of deception. For this purpose, in addition to using the capacity of verbal and non-verbal analysis methods, thermal imaging technology and new methods of spatiotemporal analysis of the thermal patterns have been used to detect concealed information in individuals. Then, based on the study design, the database consisting of 48 truth-tellers and liars who participated in a mock scenario was collected. Then, two qualitative methods of verbal and non-verbal information analysis, including standard criteria-based content analysis (CBCA) and behavioral analysis interview (BAI) scoring, were used to identify liars and truth-tellers. In order to complete the obtained results based on these two methods, using effective connectivity analysis method, physiological network analysis of communication between different areas of the face was performed in thermal images of individuals. As a result of combining quantitative and qualitative information, the final accuracy of individuals' diagnosis increased from an average of 73.61% to 79.17%. The investigation of the agreement analysis between methods by kappa coefficient and analysis of confusion matrix information indicated the existence of complementary information in various quantitative and qualitative methods to identify concealed information in individuals.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Mohammad Shahab Shahvazian; Vahid Abootalebi; Mohammad Taghi Sadeghi
Volume 6, Issue 1 , June 2012, , Pages 35-47
Abstract
With the advent of biometric knowledge, conventional methods of authentication are being replaced with biometric based methods. Recently, the use of EEG signal in biometric systems attracted increasing research attention. Only a few works have been done in this emerging of EEG-based biometry mainly focusing ...
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With the advent of biometric knowledge, conventional methods of authentication are being replaced with biometric based methods. Recently, the use of EEG signal in biometric systems attracted increasing research attention. Only a few works have been done in this emerging of EEG-based biometry mainly focusing on person identification not on person authentication. This paper examines the effectiveness of the EEG as a biometric for person authentication. In this study, the EEG signal from fifteen volunteer recorded during imagination of opening and closing fist was used. A set of AR coefficients, power of spectral bands, Energy Spectral Density, Energy Entropy and Sample Entropy were used as extracted features. The authentication system is fused at the sensor module and features to support a system which can meet more challenging and varying requirements. The utility of the sequential search methods is also experimentally studied. In the extensive experimentation on the Shalk and his colleague’s database, we demonstrate that with combination of features when using single channel EEG, the performance of system is improved in two ways of single block and multi block methods compared to other. Result of this study shows a clear vision of commercial and practical use of the brain's electrical signals in the authentication systems of future.
Cardiovascular Biomechanics
Nima Hemati; Mohammad Javad Abolhassani
Volume -2, Issue 1 , July 2005, , Pages 35-46
Abstract
Nowadays, various methods have been suggested to measure and monitor blood velocity variation in arteries and veins. Ultrasonic velocimetry is one of these methods, which is based on Doppler shift frequency measurement and the blood flow velocity calculation using Doppler shift signal. Using velocity-time ...
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Nowadays, various methods have been suggested to measure and monitor blood velocity variation in arteries and veins. Ultrasonic velocimetry is one of these methods, which is based on Doppler shift frequency measurement and the blood flow velocity calculation using Doppler shift signal. Using velocity-time curves or frequency spectrum which is system outputs, the abnormal cases and the stenosis degree can be determined. In this study, the design and prototyping of a pulsed Doppler system are investigated. The design consists of analog and digital circuits. The analog section includes Master oscillator, stimulus generator, transmitter, receiver, RF amplifier, demodulator and signal sampling circuits. Analog Doppler signal is then converted to digital codes and transferred to PC via an analog to digital converter card. The controlling of analog circuits is also implemented by the digital control unit. After data being transferred to the PC, data analysis such as fast fourier transform (FFT), monitoring of blood velocity variation with time and computation of two dimensional spectrogram are implemented by a software which was written in the Visual C++6 environment. In order to test the system, a string Doppler phantom with full electronic control was built. This phantom also can be used to test and control the quality of the other clinical ultrasonic Doppler systems.
Rehabilitation Engineering
Rahele Mohammadi; Ali Mahloojifar
Volume 7, Issue 1 , June 2013, , Pages 39-55
Abstract
A critical issue in designing a self-paced brain computer interface (BCI) system is onset detection of the mental task from the continuous electroencephalogram (EEG) signal to produce a brain switch. This work shows significant improvement in a movement based self-paced BCI by applying a new sparse learning ...
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A critical issue in designing a self-paced brain computer interface (BCI) system is onset detection of the mental task from the continuous electroencephalogram (EEG) signal to produce a brain switch. This work shows significant improvement in a movement based self-paced BCI by applying a new sparse learning classification algorithm, probabilistic classification vector machines (PCVMs) to classify EEG signal. Constant-Q filters instead of constant bandwidth filters for frequency decomposition are also shown to enhance the discrimination of movement related patterns from EEG patterns associated with idle state. Analysis of the data recorded from seven subjects executing foot movement using the constant-Q filters and PCVMs shows a statistically significant 16% (p<0.03) average improvement in true positive rate (TPR) and a 2% (p<0.03) reduction in false positive rate (FPR) compared with applying constant bandwidth filters and SVM classifier.
Speech processing
Hamid Azadi; Mohammad Ali Khalil Zade; Mohammad Reza Akbarzade Toutounchi; Hamid Reza Kobravi; Fariborz Rezaei Talab; Seyed Amir Ziafati Bagherzade; Alireza Noei Sarcheshme; Nina Shahsavan Pour
Volume 10, Issue 1 , May 2016, , Pages 41-47
Abstract
In recent years, researchers have tried hardly to diagnose Parkinson's disease through finding its relation with the patient's speech signal. Also, many studies have been performed on determining the intensity of the disease and its relation with vocal impairment measures. In this paper, we aim to assess ...
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In recent years, researchers have tried hardly to diagnose Parkinson's disease through finding its relation with the patient's speech signal. Also, many studies have been performed on determining the intensity of the disease and its relation with vocal impairment measures. In this paper, we aim to assess and compare the ability of extracting different feature sets from speech signal in order to Parkinson's disease diagnosis. Therefore, 132 features were used to measure vocal impairments from the voice signal of individuals vocalizing phoneme /a/. Then, we used RELIEF feature selection method and applied it to Support Vector Machine (SVM) classifier to choose the best feature of each class. A comparison was made between different feature sets, and finally discrimination percent 95.93 was reached to separate patients from the healthy ones using the combination of selected features. Results obtained from this research can be a very important step toward diagnosing Parkinson's disease non-invasively.
Bioelectrics
Seyed Hojat Sabzpoushan; Tina Ghodsi Asnaashari; Fateme Pourhasanzade
Volume 11, Issue 1 , May 2017, , Pages 41-49
Abstract
Cancer is one of the most important causes of mortality in human society; therefore, scientists are always looking for new ways to cope with the disease. Understanding more about the dynamics of cancerous tumors in body can help researches. Therefore, making simple models for tumor growth is important. ...
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Cancer is one of the most important causes of mortality in human society; therefore, scientists are always looking for new ways to cope with the disease. Understanding more about the dynamics of cancerous tumors in body can help researches. Therefore, making simple models for tumor growth is important. Various models have been proposed for the dynamics of cancer cell growth in the body. In some models, the interaction of different types of cells in the cancerous system is mentioned. The cells in the cancerous system include tumor, healthy, and the immune system cells. Generally, the previous models based on these three cell populations couldn’t simulate chaotic behaviors, while the biology of cancer has confirmed chaos in the system. In this paper, a model of three variables is presented and it’s shown that for some values of parameters the system can simulate chaotic behaviors. Model parameters are defined based on biological relationships, each of which plays a particular role in the dynamics of the system. To analyze the role of the parameters, a specific interval is assigned to each parameter, and by plotting the bifurcation diagram, behavioral changes of the system is observed. The results show that some of the parameters have less role in the system's behavior, and by adjusting some of them, free tumor system can be provided. Also, by setting other parameters, the system can lead to a malignant tumor. The parameters of the immune system equation have the least effect on the system’s dynamics. Regarding this finding, it can be said that applying a therapeutic approach that changes the parameters of the immune system will play a minor role in treatment. While applying therapies that change the parameters of healthy cells has the greatest effect on treatment.
Medical Instrumentation
Reza Hosseini-Ara; Amir Hossein Karamrezaei; Ali Mokhtarian
Volume 12, Issue 1 , June 2018, , Pages 41-49
Abstract
This study presents a Silicon nano bio-sensor based on modified continuum mechanics model of Euler-Bernoulli beam theory. This cantilever resonant nano-sensor works based on the shift of resonant frequency due to the adsorption of very small particles such as viruses and bacteria. To this end, the surface ...
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This study presents a Silicon nano bio-sensor based on modified continuum mechanics model of Euler-Bernoulli beam theory. This cantilever resonant nano-sensor works based on the shift of resonant frequency due to the adsorption of very small particles such as viruses and bacteria. To this end, the surface of nano bio-sensor is impregnated into a biologically active substance such as Myosin as an adsorbate layer. However, most conducted studies have ignored the effects of mass and stiffness of this adsorbate layer and nonlocal parameter, whereas these factors play a major role in changing the resonant frequency at nano-scale and the precision of mechanical nano bio-sensors. By calculating and regarding all of the mentioned effects, in this study a Silicon nano bio-sensor with a full coverage of the adsorbate layer is precisely analyzed. The results show that the calculation of nonlocal effect reduces the resonant frequency of the nano sensor, and this effect cannot be ignored in the nano-scale. It is also observed that considering the effects of the mass and stiffness of the adsorbate layer separately, may not lead to the exact answer, but the result of both of these effects should be taken into account. In fact, simultaneously considering these effects, it reduces the resonant frequency of nano sensor, which can be useful in designing and analyzing mechanical Silicon nano bio-sensors and increasing the accuracy of their detection. Finally, for the purpose of verification assessment, the numerical results were compared with the results of other studies in the full coverage of the myosin adsorbate layer, which showed complete agreement with them.
Microfluidic Biomechanics / Bio-Microfluidics
leila karami monfared; shahram talebi; mehdi mohammadiashani
Volume 17, Issue 1 , May 2023, , Pages 41-50
Abstract
Early recognition of common diseases, including cancer, plays an essential role in preventing the progression of the disease. Among the various methods that have been invented for blood monitoring in recent years, the methods based on the use of micro-scale flow have received special attention. Isolation ...
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Early recognition of common diseases, including cancer, plays an essential role in preventing the progression of the disease. Among the various methods that have been invented for blood monitoring in recent years, the methods based on the use of micro-scale flow have received special attention. Isolation of biological nanoparticles is widely used in diagnosis, treatment and care in the field of medicine. Recent research on nano-sized extracellular carriers is of interest in the field of medicine. Biological nanoparticles such as viruses, DNA, proteins and exosomes contain significant information that can help diagnose and treat diseases such as cancer. One of the practical and effective methods for separating nanoparticles is the use of viscoelastic fluid, which does not have the complications of other methods. Unlike microparticles, the number of studies in the field of bio nanoparticles is low. Since previous research in the field of nanoparticle separation lacks comprehensive numerical information about the effect of aspect ratio and polymer concentration, in this article, the viscoelastic fluid flow along with particle physics has been numerically simulated with Comsol Multiphysics software. The effective parameters including aspect ratio 1, 1.5 and 2 and polymer concentration 0.05, 0.15 and 0.25 % have been investigated in the separation of 1000 up to 100 nm particles. Separation of 300 and 500 nm particles at a concentration of 0.05% and the channel with an aspect ratio 1 and 1.5 has been obtained from the other particles. It is possible to separate the particle 100nm as exosome particle from the other particles at an aspect ratio 2 and a polymer concentration of 0.05% as the best choice
Biomedical Image Processing / Medical Image Processing
Malihe Miri; Mohammad Taghi Sadeghi; Vahid Abootalebi
Volume 8, Issue 1 , March 2014, , Pages 45-56
Abstract
Successful outcomes of Sparse Representation-based Classifier (SRC) and Sparse Subspace Clustering (SSC) in many applications motivated us to combine these methods and propose a hierarchical classifier. The main idea behind the SRC and SSC algorithms is to represent a data using a sparse linear combination ...
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Successful outcomes of Sparse Representation-based Classifier (SRC) and Sparse Subspace Clustering (SSC) in many applications motivated us to combine these methods and propose a hierarchical classifier. The main idea behind the SRC and SSC algorithms is to represent a data using a sparse linear combination of elementary signals so that those elementary signals which are similar to the data contribute mainly in the representation. In this paper, the performance of a sparse representation based classifier is improved by pre-clustering of training samples using the SSC algorithm. A twostage SRC is then designed using the resulting clusters. A test data is classified by first determining the most similar cluster. The data label is subsequently found using the second stage classifier. The performance of the proposed method is evaluated considering cancer classification problem using the 14-Tumors microarray dataset. Due to low number of data samples per each class and high dimensionality of the data, this is a challenging problem. Curse of dimensionality, overfitting of the classifier to the training data and computational complexity are the possible related problems. Our experimental results show that the proposed method outperforms some other state of the art classifiers.
Bioheat Transfer
Parisa Rahmani; Hossein Shamohammadi; Omid Abouali; Homayoon Emdad; Mohammad Faramarzi
Volume 13, Issue 1 , April 2019, , Pages 45-53
Abstract
Turbinates play an important role in conditioning of inhaled air and affect the airflow passing the nasal cavity. The purpose of this study is to investigate the effect of removing inferior turbinate on flow field, heat and moisture transfer from mucosa into the inhaled-air in a human nasal cavity and ...
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Turbinates play an important role in conditioning of inhaled air and affect the airflow passing the nasal cavity. The purpose of this study is to investigate the effect of removing inferior turbinate on flow field, heat and moisture transfer from mucosa into the inhaled-air in a human nasal cavity and comparison of them before and after the surgery. Turbinectomy was performed virtually on the computational model under the specialist’s supervision. In this study the airflow assumed to be laminar and unsteady. The nasal wall assumed to be rigid and no slip boundary condition was set. Moreover, the mucous layer assumed to be within fixed thickness in all over nasal cavity surface. The temperature and humidity distribution over the surface of mucusa are found by numerical computation. The results depict that conditioning of the nasal airway deteriorates by removing the inferior turbinate. For a specific air flow rate, both the heat and moisture flux averages decrease after surgery.
Tissue Engineering
Abdorreza Sheikh Mehdi Mesgar; Zahra Mohammadi
Volume -1, Issue 1 , June 2004, , Pages 47-55
Abstract
The conditions for synthesis of amorphous calcium phosphates (ACPs) according to the crystallization principles were described. By selecting reaction parameters correctly (low temperature, high pH, immediate removing of water and using solutions containing calcium cations and phosphate anions at low ...
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The conditions for synthesis of amorphous calcium phosphates (ACPs) according to the crystallization principles were described. By selecting reaction parameters correctly (low temperature, high pH, immediate removing of water and using solutions containing calcium cations and phosphate anions at low concentrations), full ACPs can be reproducibly synthesized. The X-ray diffraction patterns of synthesized amorphous specimens were showed a characteristic broad peak. The Ca/P ratio of the resulting precipitates was weakly dependent on the initial Ca/P ratio. Solubility of synthesized specimens in simulated osteoclastic activity conditions was showed that the rate of dissolution would be decreased with increasing crystallinity level. The synthesized amorphous calcium phosphates showed the highest dissolution rate in the simulated solution, and can be a suitable candidate for using in the field of hard tissue engineering applications.
Biomedical Image Processing / Medical Image Processing
Mohamad Reza Rezaeian
Volume 15, Issue 1 , May 2021, , Pages 47-58
Abstract
Molecular magnetic resonance imaging by tracking contrast agents based on magnetic resonance of the nucleus is considered a novel anatomical and functional diagnostic method in various medical applications due to its good spatial resolution and safe technology. In a magnetic resonance scanner, a spectroscopic ...
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Molecular magnetic resonance imaging by tracking contrast agents based on magnetic resonance of the nucleus is considered a novel anatomical and functional diagnostic method in various medical applications due to its good spatial resolution and safe technology. In a magnetic resonance scanner, a spectroscopic spectrum known as the Z-spectrum is obtained by applying a predominantly rectangular electromagnetic saturation pulse. At frequencies corresponding to the Larmor frequency, some amplitudes due to water saturation contrast factors are formed, representing saturation transfer’s effect due to chemical exchange (CEST). Chemical shifts, magnetic field heterogeneity and imaging process’s noise, while shifting the Larmore frequencies position, distorts the CEST effect. This noise is mainly modeled by the raisin distribution, which is an extent of Gaussian distribution. In this paper, an efficient method for reducing noise from the Z-spectrum and detecting the CEST effect is presented. Deionization is performed using the analytical model’s output resulting from solving the Bloch-McCannell equations and detecting the CEST effect by calculating the Bayesian likelihood function. The proposed method’s effectiveness for noise cancellation and detection the CEST effect was performed on real Z-spectra which is obtained from magnetic resonance scanners and data obtained from human tissue. The average performance of the proposed method is measured by relative mean square error between the real Z-spectrum and the noise in the signal to noise 10dB and the number of observations 5 was about four percent. The value of the first type of error (p-value) based on parametric data was less than 5% when the noise variance was more than 0.008 and the number of observations was more than 5. In this paper, a criterion for detecting the effect of CEST based on the mediation operator is proposed to evaluate the efficiency of the proposed method in proportion to the noise power and the number of observations.
Mehran Ashrafi; Farzan Ghalichi; Behnam Mirzakouchaki
Volume 9, Issue 1 , April 2015, , Pages 49-57
Abstract
Periodontal ligament (PDL) is a soft fibrous tissuewhich is located between tooth and alveolar bone. Because the tissue is softer than the surrounding tissue, tooth movement is forced to follow the movement of the soft tissue. The goal of this study is comparison of periodentium related to single and ...
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Periodontal ligament (PDL) is a soft fibrous tissuewhich is located between tooth and alveolar bone. Because the tissue is softer than the surrounding tissue, tooth movement is forced to follow the movement of the soft tissue. The goal of this study is comparison of periodentium related to single and two root teeth behavior with applying different loads. The modeling of the real 3D geometry of incisor and premolar periodentium is carried out using micro CT scan. PDL is considered as hyperelastic material and stress-strain distribution was investigated by applying different loads. The results of finite element simulation show that tooth displacement with different loading is not necessarily in direction of loading and also stress distribution show that PDL absorbs the stresses, consequently alveolar carry less stresses. Strain distribution in PDL and alveolar bone stress represents uniform distribution of force in two root tooth. The analogy of results shows the accommodation with pervious studies.
Biomechanical Motor Control / Motor Control of Human Movement
Ehsan Rashedi; Mohammad Reza Nassajian; Bahman Nasseroleslami; Mohammad Parnianpour
Volume 2, Issue 2 , June 2008, , Pages 109-122
Abstract
Human motor system is organized for execution of various motor tasks in different and flexible ways. This is mainly achieved by the way that CNS uses the redundancy in musculoskeletal system. The kinetic redundancy in human musculoskeletal systems is a significant property by which CNS achieves many ...
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Human motor system is organized for execution of various motor tasks in different and flexible ways. This is mainly achieved by the way that CNS uses the redundancy in musculoskeletal system. The kinetic redundancy in human musculoskeletal systems is a significant property by which CNS achieves many complementary goals. Following the definition and role of uncontrolled manifold for movement kinematics, the kinetic redundancy concept is explored in mathematical terms. The null space of the kinetically redundant system when certain joint Moment and/or Stiffness are needed is derived and discussed. The mathematical methods have already been developed and applied to a simpler planar model. However in this paper, the aforementioned concepts were illustrated, using a 3-dimensional 3- degree of the freedom biomechanical model of spine with 18 anatomically oriented Hill-type-model muscle fascicles. The results can shed light to the interaction mechanisms in activation patterns of muscles, seen in various tasks and exertions and can provide a significant understanding for future studies and clinical practices related to low back disorders.
Fluid-Structure Interaction in Biological Media / FSI
Farzan Ghalichi; Majid Ahmadlouy Darab; Ahmad Ramezani Saadatabadi
Volume 1, Issue 2 , June 2007, , Pages 111-117
Abstract
In order to compare the aorta-coronary and coronary-coronary bypasses blood flow fields in the Endto-Side Anastomosis, we carried out numerical simulation of three dimensional pulsatile blood flow for 50% stenosis by using FLUENT 5.2.3 software. In this study, the blood was assumed to be as the Newtonian, ...
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In order to compare the aorta-coronary and coronary-coronary bypasses blood flow fields in the Endto-Side Anastomosis, we carried out numerical simulation of three dimensional pulsatile blood flow for 50% stenosis by using FLUENT 5.2.3 software. In this study, the blood was assumed to be as the Newtonian, incompressible and homogeneous fluid. The arterial wall was also considered to be rigid. Non-existence of the secondary flows in the coronary-coronary bypass blood flow fields for various degrees of bypass grafting angles against the aorta-coronary-coronary bypass, return of total blood flow toward upstream in the coronary-coronary bypass three times over a heart cycle, high temporary oscillation in the wall shear stress magnitudes for the aorta-coronary bypass and low wall shear stress magnitudes for the coronary-coronary bypass were of the important results.
Genetic Engineering / Genetic Modification / Genetic Manioulation
Ayatollah Rezaei; Faeze Ghanati; Mehrdad Behmanesh
Volume 6, Issue 2 , June 2012, , Pages 113-122
Abstract
In this study cell growth, some physiological parameters, production of Taxol and gene expression in cell culture of hazel under effect of the magnetic field were investigated. Cells in suspension culture were treated by a 30 mT static magnetic field on days 8-11 after subculture and 4 hours each day. ...
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In this study cell growth, some physiological parameters, production of Taxol and gene expression in cell culture of hazel under effect of the magnetic field were investigated. Cells in suspension culture were treated by a 30 mT static magnetic field on days 8-11 after subculture and 4 hours each day. The results showed that while the growth rate and viability of cells weren’t affected by the magnetic field but membrane lipid peroxidation rate and H2O2 production increased. Activity of phenylalanine ammonia lyase, polyphenol oxidase and peroxidase enzymes was increased by the magnetic field compared with control. Production of phenolic compounds and Taxolin treated cells showed an increase compared to those of control cells. Magnetic field increased intracellular Taxol more than extracellurTaxol, and in treated cultures total taxol production was 2.9-fold compared to control culture. Gene expression of 1- deoxy -D- xylulose -5 - phosphate reductoisomerase involved in producing Taxol precursors and in its biosynthesis was also increased in treated cells compared to control. It appears that magnetic field by stimulating cell defense responses and inducing gene expression involved in Taxol biosynthesis has resulted in improved its production.
