Seyed Mahmoud Sakhaei; Ali Mahloojifar
Volume -2, Issue 1 , July 2005, , Pages 47-56
Abstract
The beam pattern profile of an ultrasound array is of great importance in ultrasound imaging. This profile could be enhanced by weighting the elements of array. However, this technique will decreases the signal to noise ratio (S/N) and consequently the quality of the obtained image. In this study, the ...
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The beam pattern profile of an ultrasound array is of great importance in ultrasound imaging. This profile could be enhanced by weighting the elements of array. However, this technique will decreases the signal to noise ratio (S/N) and consequently the quality of the obtained image. In this study, the S/N variation in weighting process is mathematically analyzed, and a new method is proposed to optimize the weighting parameters. The main objective of the method is to provide the desired output of the beam pattern profile of the ultrasound array, as well as the highest possible S/N. The results show that S/N decreases with increasing the main lobe width of beam pattern. The decrease of S/N by weighting in full arrays is higher than in the sparse ones. Also, reducing the focusing depth has the same effect on S/N.
Biomechanics of Bone / Bone Biomechanics
Sara Sadat Farshidfar; Mohammad Reza Mallakzadeh; Hamid Reza Yazdi
Volume 6, Issue 1 , June 2012, , Pages 49-55
Abstract
The aim of this study was to compare the contact area and pressure within medial and lateral compartments of tibiofemoral joint during internal and external rotational deformities of tibia bone. Methods: five lower extremities of fresh frozen human cadavers were tested by using a mechanical system was ...
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The aim of this study was to compare the contact area and pressure within medial and lateral compartments of tibiofemoral joint during internal and external rotational deformities of tibia bone. Methods: five lower extremities of fresh frozen human cadavers were tested by using a mechanical system was designed for the first time in IRAN to simulate the static position loading of standing on two legs in full extension knee under 400N loading along the longitudinal axis of each foot. The contact area and pressure were measured by FUJIfilm Prescale films under axial loading in neutral rotation and serial mal-rotations of tibia from 40 degrees external to 40 degrees internal mal-rotations in 10 degrees increments by tibial osteotomy. Results: contact area and lateral compartment contact pressure was not significantly affected by mal-rotations. Medial compartment contact pressure increased with external and decreased with internal mal-rotations. Changing the medial compartment contact pressure of tibiofemoral joint in various rotational alignments of tibia can be very effective in rapid growth of knee osteoarthritis symptoms specially in people with unilateral medial knee osteoarthritis.
Biomedical Image Processing / Medical Image Processing
Seyedeh Zahra Islami Rad; Reza Gholipour Peyvandi
Volume 10, Issue 1 , May 2016, , Pages 49-57
Abstract
Positron emission tomography (PET) system is used in order to diagnose physiology changes in the body. Thus, the goal of the PET studies is to obtain a good quality and detailed image of organs by the PET scanner. The PET system performance and output image quality depend on the parameters including ...
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Positron emission tomography (PET) system is used in order to diagnose physiology changes in the body. Thus, the goal of the PET studies is to obtain a good quality and detailed image of organs by the PET scanner. The PET system performance and output image quality depend on the parameters including spatial resolution, scatter fraction, sensitivity, RMS contrast and SNR which the system was evaluated based on them. In this paper, system features and tomography method for the IRI-microPET system are considered, firstly. Then, image reconstruction algorithms (MLEM, SART, and FBP) were performed on sinogram and the performance and the acquired images quality were evaluated. The radial and tangential resolutions of 1.81 mm and 1.90 mm for 18F at the center of FOV were measured. The scatter fraction of 7.1% for the mouse phantom and the sensitivity of 1.74% in 4 ns timing window was measured. Finally, images quality was compared by RMS contrast and SNR factors, which MLEM algorithm has superiorityin comparison with the other reconstructed algorithms.The acquired results from IRI-MicroPET system were compared with available commercial animal PET scanner which the results show the good agreement between data.
Tissue Engineering
Mehdi Navidbakhsh; Mehdi Sajjadi; Simzar Hosseinzade
Volume 11, Issue 1 , May 2017, , Pages 51-61
Abstract
Tissue engineering is a promising approach for developing viable alternative for current treatments of cardiovascular diseases such as autologous vessel and synthetic bypass graft transplantation. One of the major challenges in development of an applicable tissue engineered vessel is proper design of ...
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Tissue engineering is a promising approach for developing viable alternative for current treatments of cardiovascular diseases such as autologous vessel and synthetic bypass graft transplantation. One of the major challenges in development of an applicable tissue engineered vessel is proper design of scaffold. Scaffolds are served to mimic the natural in vivo environment of cells where they interact and behave according to the mechanical cues obtained from the surrounding extracellular matrix. In recent studies alginate hydrogels containing silk fibroin protein have shown sufficient biological capability for vascular cells attachment, spreading, growth and metabolic activity. The purpose of this study was to evaluate the mechanical properties of mentioned hydrogels as scaffolds for vascular tissue engineering. Elastic modulus of linear region, yield strain and stress and compliance of three types of Alginate based hydrogel with different synthesis procedures were obtained via uniaxial tensile test of dogbone shaped specimens and thick-wall cylinders stress-strain equations. Results were compared to find the optimal formulation and synthesis process for mimicing mechanical properties of native tissue. Results of this study shows that while the proposed formulation of alginate/fibroin hydrogel lacks required mechanical stiffness, flexibility and strength; hybrid dual-network hydrogels of alginate/fibroin/polyacrylamide with a two-steps synthesis process and cross-linked by Fe3+ and Ca2+ cations promote suitable mechanical properties to be used as vascular tissue engineering scaffolds. Adding polyacrylamide to alginate-firoin hydrogels increased its elastisity modulus from 46 kPa to 480 kPa with a two step gelation process which makes it more similar to arteries wall tissue mechanically.
Biomedical Image Processing / Medical Image Processing
Mahdieh Ghasemi
Volume 12, Issue 1 , June 2018, , Pages 51-61
Abstract
Parkinson’s disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. Different pathological attacks in Parkinson’s disease can be investigated by directional relations in the base spontaneous fluctuations of the brain from the resting ...
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Parkinson’s disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. Different pathological attacks in Parkinson’s disease can be investigated by directional relations in the base spontaneous fluctuations of the brain from the resting state functional magnetic resonance imaging (RS-fMRI) data. In this paper, for analyzing the directional brain network at rest, Directed Transform Function (DTF) technique with graph theory has been used in two frequency sub-bands and intra/inter group connectivities were compared by statistical analysis. The result of group comparison between PD and healthy which has been done, showed that there are more significant connections in the low frequency band in Parkinson’s disease and control group compared to high frequency band. The relation between basal ganglia and cerebellum has been disturebed in Parkinson’s disease. Furthermore, some brain regions such as left cerebellum has the most information flow in healthy group which characterized by pivotal regions which were influenced by the other brain regions, this connection became disordered in Parkinsonism.
Neural Engineering / Neuroengineering / Brain Engineering
Mohammad Reza Nazari; Mohammad Reza Daliri; Ali Motie Nasrabadi
Volume 16, Issue 1 , May 2022, , Pages 51-62
Abstract
Visual attention as a cognitive factor plays a significant role in the processing of higher-order mental information that happens in the brain and affects brain activity in various areas of the visual cortex. Among the various recording systems, local field potentials, due to their stability, robustness, ...
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Visual attention as a cognitive factor plays a significant role in the processing of higher-order mental information that happens in the brain and affects brain activity in various areas of the visual cortex. Among the various recording systems, local field potentials, due to their stability, robustness, and frequency content have received interest in brain structure and cognitive processing research, as well as brain-computer interface (BCI) systems. Hence, the extraction and interpretation of information from local field potential (LFP) signals during visual attention has been considered to control cognitive systems. Cross-frequency coupling (CFC) as one of the information encoding strategies in the brain plays a functional role in perception, working memory, and visual attention tasks. However, the role of CFC as informative features for spatial attention decoding has not been adequately investigated. This paper aims to examine spatial attention decoding using LFP signals recorded from the monkey middle temporal area (MT). For this purpose, phase-phase and phase-amplitude coupling features and machine learning algorithms have been employed. The results show that the highest decoding performance was achieved by applying selected optimal features and the support vector machine classifier (90.36%). Moreover, among the selected features, gamma-delta, gamma-alpha, and beta-delta coupling contain the most cognitive information and the most effective features to improve the decoding performance of spatial attention in the visual system. Generally, the results suggest that cross-frequency coupling of LFP signals contains significant information in spatial attention tasks, and can be used as a suitable alternative to the time-frequency features of brain signals in cognitive BCI systems.
Biomechanics / Biomechanical Engineering
Alireza Rezaie Zangene; Ramila Abedi Azar; Hamidreza Naserpour; seyyed hamed hosseini nasab
Volume 16, Issue 4 , March 2023, , Pages 51-60
Abstract
Knee joint contact force (KCF) plays a significant role in the occurrence and progression of knee osteoarthritis (KOA) disease. KCF can be used in monitoring rehabilitation progress after knee arthroplasty surgery and the design of prostheses. Currently, measuring KCF is dependent on the data extracted ...
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Knee joint contact force (KCF) plays a significant role in the occurrence and progression of knee osteoarthritis (KOA) disease. KCF can be used in monitoring rehabilitation progress after knee arthroplasty surgery and the design of prostheses. Currently, measuring KCF is dependent on the data extracted from gait laboratories. The combination of artificial neural networks (ANNs) and wearable technology can overcome the limitations imposed by lab-based analysis in measuring KCF. Therefore, the present study aimed to investigate the potential of a fully-connected neural network (FCNN) in predicting the KCF via three inertial measurement unit (IMU) sensors attached to the pelvis, thigh, and shank segments. Ten healthy male volunteers participated in this study. The 3D marker trajectories and ground reaction forces (GRF) were captured at 200 Hz and 1000 Hz sampling frequencies during level-ground walking. Using a generic OpenSim model, the KCF was estimated through static optimization. The resultant KCF estimated by the musculoskeletal model was then used as the target of the neural network, while linear acceleration and 3D angular velocity data captured by three IMUs were considered as the network inputs. The network performance was investigated at intra- and inter-subject levels. Based on our findings, the proposed network of this study enables the prediction of KCF with 89% and 79% accuracy (based on the Pearson correlation coefficient) at the intra- and inter-subject levels, respectively. The results of this study promise the possibility of using IMU sensors in predicting KCF outside the lab and during daily activities.
Biological Computer Modeling / Biological Computer Simulation
mohamood borzouei; modjtaba emadi-baygi; mohammad mardaani; hasan rabani
Volume 17, Issue 1 , May 2023, , Pages 51-60
Abstract
It is critical for developing treatment strategies to investigate and analyze the growth dynamics and changes of invasive tumors in response to various microenvironmental conditions. When a tumor reaches its maximum amount of non-vascular growth, its cells compete for more food and oxygen sources, triggering ...
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It is critical for developing treatment strategies to investigate and analyze the growth dynamics and changes of invasive tumors in response to various microenvironmental conditions. When a tumor reaches its maximum amount of non-vascular growth, its cells compete for more food and oxygen sources, triggering complex processes in its evolution. Understanding the distribution of oxygen in the tumor environment is critical for unraveling the complexities of cancer progression. Existing physical models for studying oxygen distribution in tumors are based on reaction-diffusion equations, which include factors such as the formation and distribution of the new vascular network. In this study, we presented a computational model to investigate the distribution of oxygen in a hypoxic tumor based on the formation of the vascular network, which has fewer limitations and computational complexity than many common methods and reduces the volume of calculations. When complete with sufficient clinical data, this model can lead to the development of efficient tools in the treatment strategy of some cancers.
Human Movement Modeling
Mehdi Yousefi Azar Khanian; Seyed Mohammad Reza Hashemi Golpayegani; Mostafa Rostami
Volume 13, Issue 1 , April 2019, , Pages 55-68
Abstract
Recently, analysis of the human postural stability has gained increasing interest. This is mainly due to the necessity of understanding the self-organization mechanisms in this system activated in response to any motion pattern. The extraction of effective indicators from this system could help ...
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Recently, analysis of the human postural stability has gained increasing interest. This is mainly due to the necessity of understanding the self-organization mechanisms in this system activated in response to any motion pattern. The extraction of effective indicators from this system could help clinicians to diagnose patients’ postural disorders and guide the rehabilitation processes. The center of pressure (CoP) signal, as a collective variable, contains information from the human equilibrium system. Through the CoP trajectory production, various control mechanisms are activated at different time intervals, which is equivalent with emerging different basin of attractors in the phase space. The dynamical coordination of this system patterns determines how system switches between these attractors. In this paper, first to quantify the local information of CoP, two indicators are defined; "local correlation dimension (LCD)" and "phase dynamic coordination (PDC)". Then, for a designed experiment, the local behavior pattern of CoP time series is calculated based on the suggested indicators. Next, by designing a model that can generate rich dynamics with multiple attractors, we attempt to follow data behavioral changes. The proposed model is map based. The model parameters are tuned by PCD to follow the pattern of sub-attractors changes with the system LCD. Tracking the behavioral patterns of the posture system is one of the prominent results of this research. The proposed model not only can follow the local behavior of system, but also follows the global dynamics. Accordingly, the similarity of the decreasing-increasing trend of the correlation dimension variations for the model output and data demonstrates the variations of system’s degrees of freedom in the test trials. The proposed model is the first behavioral model for the posture system, which can be used to quantify the variation of information in other biological systems based on the proposed methods.
Biomedical Image Processing / Medical Image Processing
Maryam Afzali; Emadoddin Fatemizadeh; Hamid Soltanian Zadeh
Volume 7, Issue 1 , June 2013, , Pages 57-64
Abstract
Diffusion tensor magnetic resonance imaging (DTMRI) is a non-invasive method for investigating the brain white matter structure. It can be used to evaluate fiber bundles in the brain but in the regions with crossing fibers, it fails. To resolve this problem, high angular resolution diffusion imaging ...
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Diffusion tensor magnetic resonance imaging (DTMRI) is a non-invasive method for investigating the brain white matter structure. It can be used to evaluate fiber bundles in the brain but in the regions with crossing fibers, it fails. To resolve this problem, high angular resolution diffusion imaging (HARDI) with a large number of diffusion encoding directions is used and for reconstruction, the Q-ball method is applied. In this method, orientation distribution function (ODF) of fibers can be calculated. Mathematical models play a crucial role in the field of ODF. For instance, in registering Q-ball images for applications like group analysis or atlas construction, one needs to interpolate ODFs. To this end, principal diffusion directions (PDDs) of each ODF are needed. In this paper, PDDs are defined as vectors that connect the corresponding local maxima of ODF values. Then, ODFs are interpolated using PDDs.We find the principal direction of ODF of the dataset to be interpolated and then rotate it to lie in the direction of the reference dataset. Now that ODFs are parallel, we apply linear interpolation to generate interpolated data. The proposed method is evaluated and compared with previous protocols. Experimental results show that the proposed interpolation algorithm preserves the principal direction of fiber tracts without producing any deviations in the tracts. It is shown that changes in the entropy of the interpolated ODFs are almost linear and the bloating effect (blurring of the principal directions) can be removed.
Tissue Engineering
Karim Asgarzadeh Tabrizi; Fariba Ourang
Volume -1, Issue 1 , June 2004, , Pages 57-64
Abstract
Gelatin is a protein which is derived from the organic constituent of bone (collagen). Combination of this protein with the inorganic constituent of bone (hydroxyapatite) may provide closer properties to the natural bone. In this study, a biodegradable composite scaffold based on gelatin and hydroxyapatite ...
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Gelatin is a protein which is derived from the organic constituent of bone (collagen). Combination of this protein with the inorganic constituent of bone (hydroxyapatite) may provide closer properties to the natural bone. In this study, a biodegradable composite scaffold based on gelatin and hydroxyapatite was prepared as a substitute for bone tissue. To increase the biocompatibility of this, composite, its fabrication was carried out without using any organic solvent. Porosities obtained were spontaneously achieved without any porogen. The pore morphology indicated a high interconnectivity with diameters ranging from 50 to 200 micrometers, which seems appropriate for bone tissue engineering applications. In order to study the biocompatibility of the scaffolds, mouse fibroblastic cells were used. After 24-hour cell culture period in vitro, suitable cell attachment was observed showing high biocompatibility for all the samples. Further examinations demonstrated that the best biocompatibility is obtained for the composite of 50 wt% hydroxyapatite and 50 wt% gelatin.
Neuro-Muscular Engineering
Sahar Babaei; Ali Maleki
Volume 8, Issue 1 , March 2014, , Pages 57-68
Abstract
Nowadays real time motion tracking have been receiving considerable attention in many applications and research fields such as rehabilitation, medicine and treatment. Recently MEMS accelerometers play an important role to attend desired result for these applications. This paper presents a new design ...
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Nowadays real time motion tracking have been receiving considerable attention in many applications and research fields such as rehabilitation, medicine and treatment. Recently MEMS accelerometers play an important role to attend desired result for these applications. This paper presents a new design for angle measurement device based on accelerometer sensor and Bluetooth module. Using Bluetooth module in addition to providing minimally obtrusive recording, allows you to connect to your personal computer and mobile quicker and easier. This system has made up of 2 complete 3 axis accelerometer ADXL330, which by giving sufficient data in 3D space allows us to investigate joint angle with DCMR method. The mentioned method in dynamic recording remarkably has less error in comparison to CMR method. As one application for this system, determination of elbow joint angle is studied. Eventually experimental recording of elbow joint angle in static and dynamic condition was done by applying CMR method. With reference to electrogoniometer output the maximum static and dynamic error were obtained respectively 3 and 6.1 degrees.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Saleh Lashkari; Mohammad Ali Khalilzadeh; Seyed Mohammad Reza Hashemi Golpayegani
Volume 9, Issue 1 , April 2015, , Pages 59-69
Abstract
Using methods based on nonlinear dynamics such as Poincare Section, can be useful in detecting dynamic biological systems. Selecting a suitable Poincare surface is a critical step in data analysis. Often finding an appropriate position for Poincare section needs to set different parameters. When the ...
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Using methods based on nonlinear dynamics such as Poincare Section, can be useful in detecting dynamic biological systems. Selecting a suitable Poincare surface is a critical step in data analysis. Often finding an appropriate position for Poincare section needs to set different parameters. When the geometry of Poincare surface picks the information related to the stretching and folding, a better discrimination can be performed for the system states. The objective of this paper is to study the effect of position and degree of Poincare surface in Epileptic Seizure Detection. The Poincare surface resulting in the best classification is selected as the optimal section. Accordingly, the phase space of the EEG Segments Reconstructed in three dimension, firstly. Then, a set of Poincare surfaces with 400 different conditions of degree selected to cut the trajectory and Geometric Features Extracted from the points of intersection on each surface. Afterward, extracted features from the Poincare section are applied to SVM classifier. Pearson correlation analysis was performed to analyze the relationship between the classification performance and degree of Poincare section. Certain behavior can be observed by increasing the Surface degree in output classifier. In this way, the increasing and then decreasing pattern were observed by increasing the Surface degree in two Directions of Surface. The results showed that the equation of optimal Poincare Section for m=12 and n=6 gives the accuracy of 96.6%.
Masume Saljuqi; Peyvand Ghaderyan
Volume 15, Issue 1 , May 2021, , Pages 59-71
Abstract
In the recent years, the diagnosis of Neurodegenerative Diseases (NDDs) has been one of the most challenging problems in the medical fields. Amyotrophic Lateral Sclerosis (ALS), Parkinson's Disease (PD) and Huntington's Disease (HD) are a group of neurological disorders affecting the quality of patient’s ...
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In the recent years, the diagnosis of Neurodegenerative Diseases (NDDs) has been one of the most challenging problems in the medical fields. Amyotrophic Lateral Sclerosis (ALS), Parkinson's Disease (PD) and Huntington's Disease (HD) are a group of neurological disorders affecting the quality of patient’s life. Occurrence of these diseases is due to the deterioration of motor neurons, causing human gait disturbance and asymmetry between the right and left limbs. For this purpose, in this paper various gait signals namely stride, swing, and stance intervals (from both legs) have been decomposed using a Matching Pursuit (MP) algorithm. Then, two sets of differential and dynamic features have been extracted from the MP coefficients in order to quantify the amount of divergence between both limbs. Finally, the principal components of these features have been fed as an input to sparse Non-Negative Least Squares (NNLS) classifier. The proposed algorithm has been evaluated using the gait signals of 16 healthy control subjects, 13 patients with Amyotrophic Lateral Sclerosis (ALS), 15 patients with Parkinson’s Disease (PD) and 20 patients with Huntington’s Disease (HD). The results showed that the proposed method has achieved high average accuracy rates of 84.10%, 86.67%, and 91.43% for ALS, PD, and HD detection, respectively.
Cell Biomechanics / Cell Mechanics / Mechanobiology
Naser Mehrshad; Mohammad Hasan Ghasemian Yazdi
Volume 1, Issue 2 , June 2007, , Pages 119-129
Abstract
Simple cells in primary visual cortex respond to the local, oriented edge segments within their receptive fields. In this study, we present a new edge detection method based on the computational model of these cells. Firstly, the response of a set of simple cells for a number of different preferred orientations ...
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Simple cells in primary visual cortex respond to the local, oriented edge segments within their receptive fields. In this study, we present a new edge detection method based on the computational model of these cells. Firstly, the response of a set of simple cells for a number of different preferred orientations are calculated. Then, the intensity gradient for each pixel is obtained using the linear summation of these responses. Some parameters of simple cell computational model are calculated in such a way that a set of goals (good detection, good localization and only one response to a single edge) achieving for the resulting operator. Considering the properties of medical images, the proposed operator is useful for medical image edge detection. The synthesis and medical images with their associated ground truth edge maps are used to assess performance of the proposed method. The results obtained from the proposed method are found to be better and more stable with respect to the input parameters than those from many well known edge detectors (e.g. Canny edge detector).
Bioelectromagnetics
Hadi Tavakoli; Ali Motie Nasrabadi; Seyed Mohammad Firouzabadi; Mehri Kaviyani Moghaddam
Volume 6, Issue 2 , June 2012, , Pages 123-131
Abstract
During recent years, the environment has been enormously changed by the wide range of magnetic fields. Therefore, comprehensive studies are being done for investigating their biological effects. The effects such as inhibition of bioelectric activity of neurons which is shown by evidence, like decreasing ...
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During recent years, the environment has been enormously changed by the wide range of magnetic fields. Therefore, comprehensive studies are being done for investigating their biological effects. The effects such as inhibition of bioelectric activity of neurons which is shown by evidence, like decreasing in the firing frequency or decreasing in the amplitude of action potential, have been shown. To notify and investigate these effects, the theory of “biological windows” have been proposed and considered. The effects of amplitude and/or frequency of magnetic field have been pointed in some research. In this study, regarding the behavior of nervous system, which has non-linear dynamic behavior, we study the behavior of nervous system under exposure to magnetic field. We investigate whether the low frequency field is able to affect the dynamic of nerve cells and to have influence on non-linear features of signal. We used 6 environmental intensities and 6 cells have been used in each intensity, and by calculating some of non-linear features of action potential such as Higuchi Dimension and Return map of signal, during the time and in some different intensities of magnetic fields, It was observed that all intensities magnetic fields lead to increasing in Higuchi Dimension and increasing in the scattering of the Return map of signal. Of course these effects has been more observed in the middle band of frequency which has been confirmed by the theory of ‘frequency window’ effect of magnetic fields, which it has been noticed and discussed in last two decades.
Speech processing
Ayoub Daliri; Farzad Towhidkhah; Shahriar Gharibzadeh; Yaser Shekofteh
Volume 2, Issue 2 , June 2008, , Pages 123-129
Abstract
Speech production is one of the most complicated physiological systems including different subsystems. These subsystems must work together in a synchronous manner. One of the important sub-systems is the jaw. Although different models have suggested for jaw, no suitable model has been proposed yet to ...
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Speech production is one of the most complicated physiological systems including different subsystems. These subsystems must work together in a synchronous manner. One of the important sub-systems is the jaw. Although different models have suggested for jaw, no suitable model has been proposed yet to consider the interactions between muscles, bones and nervous system. In this paper, using Spring-Damper-Mass and a nonlinear concept, we introduced a novel model for jaw movement during speech production. Experimental data were used to estimate the model parameters. Computer simulation results showed that the model could generate the jaw movement patterns similar to those observed in physiological behavior. Generality and simplicity of the model are two model features useful for more investigation of the jaw movement in different tasks.
Nano-Biomaterials
Rouzbeh Kazemzadeh; Ali Asghar Behnamghader; Saeed Hesaraki; Fateme Hazrati
Volume 3, Issue 2 , June 2009, , Pages 127-133
Abstract
Magnesium-contained Hydroxyapatite Nano powder was synthesized by wet chemical method using calcium nitrate tetra hydrate, magnesium nitrate hexa hydrate and di ammonium hydrogen phosphate in the presence of Glutamic acid. According to thermal analysis (STA) findings the samples were calcinated at specific ...
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Magnesium-contained Hydroxyapatite Nano powder was synthesized by wet chemical method using calcium nitrate tetra hydrate, magnesium nitrate hexa hydrate and di ammonium hydrogen phosphate in the presence of Glutamic acid. According to thermal analysis (STA) findings the samples were calcinated at specific temperatures and characterized by XRD, FTIR and TEM analysis. XRD results showed the that b-TCP ((Ca1-xMgx)3(PO4)2) was the dominant phase at 920°C. No characteristic peaks of hydroxyapatite were observed at that temperature. In contrast, the sample which was synthesized in the absence of Glutamic acid, contained both hydroxyapatite and b-TCP phase. The Findings showed a rapid decline in degree of crystallinity at 90°C with presence of Glutamic acid in reaction media. Transmission electron microscopy (TEM) observations on heat treated samples at 480°C revealed that using Glutamic acid has noticeable effect on crystallite size instead of its growth orientation. Dimensions of biomimetic nanoparticles as observed by TEM were 150x60nm and in the witness sample was 500x150nm. According to Scherrer formula for crystallite size, the size of the witness sample was calculated about 40nm. However, because of low degree of crystallinity it was impossible to calculate the size of Glutamic contained samples.
Biomechanics / Biomechanical Engineering
Mostafa Haj Lotfalian; Mohammad Hadi Honarvar
Volume 14, Issue 2 , July 2020, , Pages 133-142
Abstract
Margin of stability is a method to assess the dynamic stability in the clinic and laboratory, which is influenced by position and linear velocity of the center of mass (CoM). In this study, the stability factor was calculated by the margin of stability (MoS) method and was used as a cost function to ...
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Margin of stability is a method to assess the dynamic stability in the clinic and laboratory, which is influenced by position and linear velocity of the center of mass (CoM). In this study, the stability factor was calculated by the margin of stability (MoS) method and was used as a cost function to plan movement trajectory of sit to stand. 10 healthy young men were selected in this study and their sit to stand movement were filmed by Optitrack motion capture system. A two-dimensional and four-segment model was defined based on the governing equations of motion to calculate position of CoM, joints torque and using that in optimization process. After calculating the subject’s stability factor by MoS method, the time integral of MoS (C1), the maximum and minimum of MoS (C2) and the time integral of the square of MoS (C3) were defined as the cost functions. genetic algorithm was used to find the optimal model. To determine the quality of predicted trajectories and compare it with the subject’s pattern, root mean square error (RMSE) was used. According to the results of this study, a model which was optimized by C3, predicted the movement trajectory of subjects with 19 and 40 percent less error than C1 and C2 respectively.Nevertheless, none of the models could correctly reconstruct the subjects’ movement trajectory. In a nutshell, using MoS exclusively as a cost function, is not a good choice to predict and plane the trajectory of whole-body movements.
Saeed Rashidi; Ali Fallah; Farzad Towhidkhah
Volume 4, Issue 2 , June 2010, , Pages 135-148
Abstract
Many methods are introduced for estimating the similarities or differences of time signals. One of theses methods, DTW algorithm, is also a utility for other domains including classification, data mining and matching regions between two time signals. DTW algorithm minimizes points distance between two ...
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Many methods are introduced for estimating the similarities or differences of time signals. One of theses methods, DTW algorithm, is also a utility for other domains including classification, data mining and matching regions between two time signals. DTW algorithm minimizes points distance between two signals by contracting or expanding the time axes to find the corresponding points. In this paper, with modification of the local constraints in DTW, a powerful method is proposed for measuring the global or local similarities between two signals. In addition to increasing the accuracy of signals distance measurements and decreasing the classification error, proposed algorithm is more stable than classic DTW against variations of structure and time signal source. The proposed method for dynamic signature verification was applied to a dataset of signatures from Turkish, Chinese and English people. The results of the experiments based on Fisher, Parzen Window and Support Vectors Machine classifications, showed that equal error rate (EER) is 1.46% and 3.51% with universal threshold for random and skilled forgeries, respectively.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Mehdi Abdossalehi; Ali Motie Nasrabadi; Seyed Mohammad Firouzabadi
Volume 7, Issue 2 , June 2013, , Pages 143-153
Abstract
In this study, electroencephalogram (EEG) signals have been analyzed in positive, negative and neutral emotions. Here it is supposed that the brain has different independent sources during an emotional activity which will be extractable by Independent Component Analysis (ICA) algorithm. For resolving ...
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In this study, electroencephalogram (EEG) signals have been analyzed in positive, negative and neutral emotions. Here it is supposed that the brain has different independent sources during an emotional activity which will be extractable by Independent Component Analysis (ICA) algorithm. For resolving the illposeness problem of extracted components by ICA algorithm, first these sources were sorted by Shannon entropy and then the features of Katz fractal dimension and the first local minimum of the mutual information based on the time delay (tau) have been extracted for representing determinism. The results show that the determinism ratio of the sorted sources has significant difference during the time in three emotional states: positive, negative and neutral. The determinism ratio increases in neutral, negative and positive emotional states, respectively.
Cardiovascular Biomechanics
Hamed Khalesi; Hanie Niroomand Oscuii; Farzan Ghalichi
Volume 5, Issue 2 , June 2011, , Pages 143-149
Abstract
Prediction of the relationship between different types of mechanical loading and the failure of the intervertebral disc is so important to identify the risk factors which are difficult to study in vivo and in vitro. On the basis of finite element methods some of these issues may be overcome enabling ...
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Prediction of the relationship between different types of mechanical loading and the failure of the intervertebral disc is so important to identify the risk factors which are difficult to study in vivo and in vitro. On the basis of finite element methods some of these issues may be overcome enabling more detailed assessment of the biomechanical behavior of the intervertebral disc. The objective of this paper is to develop a nonlinear axisymmetric poroelastic finite element model of lumbar motion segment and show its capability for studying the time-dependent response of disc. After comparison of the response of different models in quasi-static analysis, the poroelastic model of intervertebral disc is presented and the results of short-term, long-term creep tests and cyclic loading were investigated. The results of the poroelastic model are in agreement with experimental ones reported in the literature. Hence, this model can be used to study how different dynamic loading regimes are important as risk factors for initiation of intervertebral disc degeneration.
Medical Instrumentation
Farnaz Fahimi Hanzaee; Mohammad Mehdi Ahmadi
Volume 12, Issue 2 , September 2018, , Pages 147-159
Abstract
Nowadays, implantable electrical neural stimulation is extensively used to treat or alleviate certain brain-related health conditions, such as in deep brain stimulation (DBS) or in vagus nerve stimulation (VNS). In this paper, we present a digital controller block, designed for a neuroelectrical stimulator ...
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Nowadays, implantable electrical neural stimulation is extensively used to treat or alleviate certain brain-related health conditions, such as in deep brain stimulation (DBS) or in vagus nerve stimulation (VNS). In this paper, we present a digital controller block, designed for a neuroelectrical stimulator chip dedicated for a brain implant.The presented design is very power and area-efficient and provides a great flexibibity in programming the specifications of the stimulation pulses. The duration of each stimulation pulse can programmed to be from 4 µs to 4 ms, and the amplitude of each pulse could be from 4 µA to 1 mA. The stimulation pulses could be either monophasic or biphasic, In addition, in biphasic stimulation, the priority of the cathodic pulse over the anodic pulse, or vice versa, could be pragrammed. The interphase delay between the anodic and cathodic phases could be programmed to be between 4 µs and 512 µs. The controller controls 16 stimulation sites, four of which can be stimulated simoultaneualy. The 16 stimulation sites are divided into four groups, each of which is stimulated by a current-controlled stimulation circuit. Each stimulation circuit is controlled by a local digital controller (LDC), which receives its data from a global digital controller (GDC). The designed controller blocks have been implemented and tested on a Spartan-6 field-programmable gate array (FPGA) board, before being implemented as an application-specific integrated circuit (ASIC) layout. The ASIC circuit has been designed using 0.18-µm CMOS technology. Based on the layout, each LDC occupies an area of 19,160 µm2 and consumes 12 µW of power from a 1.8V supply. On the other hand, the GDC takes up an area of 4,246 µm2 and consumes 8.2 µW of power. We have also created a graphical user interface (GUI) to be able to program the stinulation chip.
Bioelectrics
Farzaneh Keyvanfard; Abbas Nasiraei Moghaddam
Volume 13, Issue 2 , August 2019, , Pages 147-158
Abstract
Brain as the most complex organ in the human body has been investigated from various aspects. The greatest origin of this complexity is due to the fact that, despite the fixed architecture of brain structure (physical connections), the functional connectivity is in a constantly changing state, resulting ...
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Brain as the most complex organ in the human body has been investigated from various aspects. The greatest origin of this complexity is due to the fact that, despite the fixed architecture of brain structure (physical connections), the functional connectivity is in a constantly changing state, resulting to different behaviors. In many mental diseases, both brain structural and functional connectivities and their relationship are changed and cause different symptoms. Investigation of brain connectivity variations in the disease may help to better understanding of the relationship between brain structure and function. One of the most severe and debilitating brain disorders is Schizophrenia in which both brain structure and function are involved. Among all available methods, multimodal analysis of data has been recently gained great interest to provide the capability of extracting association between separate neuroimaging data. However, due to their voxel based viewpoint, relationship between brain connectivities cannot be inferred. In this study, the joint independent component analysis (jICA) has been proposed to investigate the relationship between brain functional and structural connectivity. We applied the suggested approach to combine functional and structural connectivity, in order to assess abnormalities underlying schizophrenic patients relative to healthy people. The findings suggest that the correspondence between brain function and structure is not necessarily one-to-one. The results also indicated that variations in several structural fibers, such as superior longitudinal fasciculus and inferior longitudinal fasciculus, are associated with functional changes in the temporal and frontal lobes. Besides, analyzing the nodal strength and shortest path length in the obtained subnetworks demonstrates that the functional subnetworks efficiency in parallel information transfer in schizophrenic patients is reduced. Overall, the outcomes point out the capability of the proposed method to better understanding of brain functional and structural connectivity association and its variations in brain disorders.
Medical Instrumentation
Rasool Baghbani; Mohammad Hasan Moradi
Volume 10, Issue 2 , August 2016, , Pages 149-160
Abstract
In this paper a new idea is suggested for designing an appropriate bio-impedance sensor in the form of a biopsy forceps to measure the electrical properties of the tissues inside the body. First, by analytically solving the Laplace equation for wedge-shaped tissue in the mouth of the forceps, the relationship ...
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In this paper a new idea is suggested for designing an appropriate bio-impedance sensor in the form of a biopsy forceps to measure the electrical properties of the tissues inside the body. First, by analytically solving the Laplace equation for wedge-shaped tissue in the mouth of the forceps, the relationship between electric potential (results from excitation current) in different points on the tissue surface and the electrical properties of the tissue are obtained. Then, to evaluate the designed bio-impedance forceps using the finite element method and the experimental data obtained for different tissues by Gabriel et al., modeling and simulation were done and it was found that the voltages obtained for all of the tissues inside the mouth of the forceps at different frequencies from 50 Hz to 5 MHz, are consistent with that of the analytical method. To investigate the influence of the opening angle of the forceps, measurements were done at different angles and it was found that for small opening angles, measurements are more accurate. Also, electrical properties were measured by changing the size and shape of the tissue and it was found that the designed forceps is non-sensitive and robust to the changes of the volume and shape of the tissue. A prototype of the designed bio-impedance forceps was fabricated. The forceps was experimentally validated by measuring conductivity of the Phosphate Buffered Saline (PBS) solution with different concentrations at frequency range of 50KHz to 1MHz using an impedance analyzer system. To examine the accuracy of measured conductivity values, the Van Der Pauw method was implemented and electrical conductivity of the PBS was measured again. Results showed that measured conductivities by means of the bio-impedance forceps were accurate with an error less than 4%.
