Biomedical Image Processing / Medical Image Processing
Maede Hadinia; Reza Jafari
Volume 4, Issue 4 , June 2010, , Pages 317-326
Abstract
This paper presents image reconstruction in Diffuse Optical Tomography (DOT) using a high-order finite element method. DOT is a non-invasive imaging modality for visualizing and continuously monitoring tissue and blood oxygenation levels in brain and breast. Image reconstruction in DOT leads to an inverse ...
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This paper presents image reconstruction in Diffuse Optical Tomography (DOT) using a high-order finite element method. DOT is a non-invasive imaging modality for visualizing and continuously monitoring tissue and blood oxygenation levels in brain and breast. Image reconstruction in DOT leads to an inverse problem consisting of a forward problem and an iterative algorithm. The inverse problem in DOT systems is ill posed and depends on the accuracy of the forward problem. An accurate model, that describes the light transmission in tissue is required and can increase the spatial resolution. Using first order finite elements in the forward problem, numerical results are converged to the exact solution with increasing the number of elements. However, increasing the number of elements may cause a critical issue in the ill-posed inverse problem. This paper focuses on applying the high-order finite element method without increasing the number of elements, and image reconstruction is accomplished. The forward problem results are compared with analytical solutions. Images of absorbers reconstructed using this method are presented.
Cardiovascular Biomechanics
Mansour Alizadeh; Iman Mohebbi Nejad
Volume 2, Issue 4 , June 2008, , Pages 317-324
Abstract
Mechanical characteristic of arteries is very important for stent producing and cardiovascular implants. In this study mechanical behavior of a piece of left anterior descending coronary artery with specified dimension and separated layers which was prepared by holtzapfel and tested under tensile test ...
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Mechanical characteristic of arteries is very important for stent producing and cardiovascular implants. In this study mechanical behavior of a piece of left anterior descending coronary artery with specified dimension and separated layers which was prepared by holtzapfel and tested under tensile test bas been considered. Ogden hyperelastic model has been implemented for the experimental data and related parameters were obtained. These parameters have been optimized. The obtained results showed that by using the same experimental data the Ogden model can be fitted well with holtzapfel model and the errors fall within acceptable range.
Biomedical Image Processing / Medical Image Processing
Abbas Biniaz; Fatemeh Abdolali; Reza Aghaeizadeh Zoroofi; Omid Haji Maghsoudi; Yoshinobu Sato
Volume 12, Issue 4 , January 2019, , Pages 317-329
Abstract
Wireless capsule endoscopy is a non-invasive diagnosis method which allows recording a video as the capsule travels through the gastrointestinal tract. The practical drawback is producing a long clinical video up to 8 hours and it takes about 2 hours to review the exam by an experienced expert. Video ...
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Wireless capsule endoscopy is a non-invasive diagnosis method which allows recording a video as the capsule travels through the gastrointestinal tract. The practical drawback is producing a long clinical video up to 8 hours and it takes about 2 hours to review the exam by an experienced expert. Video summarization methods can reduce the time required by experts and errors in manual interpretation. This paper presents an automatic method based on unique properties of adaptive singular value decomposition through sliding window that can reduce the long annotation time. By utilizing these properties, we are able to summarize a WCE video by outputting a motion video summary. Moreover, we apply an effective approach based on adaptive contrast diffusion to correct uneven illumination that deal with the low contrast generally caused by poor visibility conditions of the GI tract, WCE power and its structure. Experimental results on WCE videos indicate that a significant reduction in the review time is feasible. Quantitative and qualitative results of summarization show the effectiveness of proposed method that can be adapted to various clinical applications, such as training of young physicians, computer assisted diagnosis, medical decision support or medical document management.
Biological Systems Modeling
Seyede Fatemeh Ghoreishian Amiri; Mohammad Pooyan
Volume 14, Issue 4 , February 2021, , Pages 321-331
Abstract
Parkinson's disease (PD) is a neurological disorder that mainly affects dopamine-producing neurons and motor system. The most obvious symptoms of PD are tremor, slow movement, stiffness and difficulty with walking. Walking in PD is slower than normal walking. In this paper, the gait in patients ...
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Parkinson's disease (PD) is a neurological disorder that mainly affects dopamine-producing neurons and motor system. The most obvious symptoms of PD are tremor, slow movement, stiffness and difficulty with walking. Walking in PD is slower than normal walking. In this paper, the gait in patients with PD is modeled by a mathematical and computational method. This model includes structures which are involved in PD, such as basal ganglia, thalamus, cortex, supplementary motor area (SMA), muscle and joint-load dynamics. The output of the model is walking speed in PD. The output value is 0.83 m/s, which is in the range reported by clinical results (0.18-1.21 m/s). Some methods which increase the gait speed in PD are investigated too. These methods include deep brain stimulation, drug prescription and strengthening the muscles. The results show that each of these methods will improve the gait speed, in fact, by using these methods, the value of output increases and approaches the walking speed range in healthy individuals (1.36-1.30 m/s). Moreover, the effect of rigidity on gait speed is studied; it has been observed that the stiffness and speed of the gait are inversely related. Finally a control method is offered which improve the gait speed by increasing the magnitude response of the closed-loop system.
Neuro-Muscular Engineering
Hesam Moradkhani; Vahid Shalchyan
Volume 10, Issue 4 , January 2017, , Pages 325-337
Abstract
P300 Speller as a most commonly used brain–computer interface (BCI) has been able to provide simple communication capabilities for people with severe motor or speech disabilities in order to have a better interaction with the outer world over the past years. Checker-board paradigm introduced by ...
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P300 Speller as a most commonly used brain–computer interface (BCI) has been able to provide simple communication capabilities for people with severe motor or speech disabilities in order to have a better interaction with the outer world over the past years. Checker-board paradigm introduced by Townsend et al. [1] is one of the most practical alternatives for row-column paradigm, enhancing the performance of the speller by preventing row-column induced errors. In this study, we investigated the effect of substituting presentation of an emoji stimulus instead of flashing the characters in the performance of a checker-board P-300 speller. The performance of the proposed paradigm was evaluated and compared to the traditional stimuli in checker-board paradigm in an online experiment over ten healthy subjects. For each paradigm, the recorded data from an offline session was used to calibrate the speller classifier; and consequently, the classification accuracy was calculated over online sessions. The proposed paradigm, showed 14% enhancement in classification accuracy with respect to the checker-board paradigm. The results of this study obviously showed that the stimuli obtained by presenting emoji instead of character flashing, effectively improved the speller classification accuracy.
Spinal Biomechanics
Iraj Dehghan Hamani; Navid Arjmand
Volume 11, Issue 4 , February 2018, , Pages 327-335
Abstract
Spinal diseases are prevalent and costly. Excessive mechanical loads on the spine play a crucial role in the etiology of back disorders. To estimate spinal loads one needs to calculate unknown muscle forces through either an optimization or EMG-driven approach. Both approaches involve several assumptions ...
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Spinal diseases are prevalent and costly. Excessive mechanical loads on the spine play a crucial role in the etiology of back disorders. To estimate spinal loads one needs to calculate unknown muscle forces through either an optimization or EMG-driven approach. Both approaches involve several assumptions and simplifications regarding anatomy of muscles, mechanical properties of the spinal tissues, and estimation of the muscle forces. An alternative approach is to estimate spinal loads through effect of muscle forces, i.e., kinematics generated by muscles rather than forces generated by muscles. The present study hence aims to estimate spinal loads using a detailed finite element (FE) model of the T12-S1 spine driven by kinematics obtained through upright x-ray imaging. For this, kinematics (angular and translational displacements) of the T12 through S1 vertebrae were first measured in vivo in three healthy individuals when performing flexion from relaxed upright posture. The measured kinematics were subsequently prescribed to the FE model to estimate load sharing among the joint structures. In agreement with the measured data, the L1-L2, L2-L3, L3-L4 and L4-L5 average intradiscal pressure was estimated to be ~2.6, ~2.8, ~2.1 and ~2 MPa in flexion, respectively.
Implant / Implant's Designing & Manufacturing
Shima Bahramizadeh-Sajadi; Hamid Reza Katoozian; Alireza Baradaran-Rafii; Miguel-Angel Ariza-Gracia; Philippe Buchler
Volume 15, Issue 4 , March 2022, , Pages 329-339
Abstract
Keratoconus (KC) is a non-inflammatory and degenerative disease of the cornea. It is manifested by the formation of cone-shaped regions accompanying severe eyesight issues. Implantation of intrastromal corneal ring segments (ICRS) is a popular treatment to improve visual acuity. Controversies exist ...
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Keratoconus (KC) is a non-inflammatory and degenerative disease of the cornea. It is manifested by the formation of cone-shaped regions accompanying severe eyesight issues. Implantation of intrastromal corneal ring segments (ICRS) is a popular treatment to improve visual acuity. Controversies exist over restoring functionality of different ICRSs. In this study, numerical models were used to quantify the mechanical and optical effects of different ICRSs on a reference cornea with central cone. Finite element (FE) simulations were used to simulate the implantation of two classes of ICRS sets common in clinical settings: a) single segment arcs of 360º (1×360), 350º (1×350), 320º (1×320), and, b) symmetric double-segment arcs of 160º each (2×160), 150º each (2×150), 120º each (2×120), and 90º each (2×90). Results showed that implantation of symmetric double-segment arcs caused the symmetric displacement and stress distribution contours on both anterior and posterior corneal surfaces. This study shows the potential impact of a detailed mechanical analysis of ICRS placement and represents a first step toward the development of an evidence-based nomogram for the different implantation techniques and the optimization of the surgical intervention based on patient-specific modeling.
Gait Analysis
Samane Moeini Sedeh; Navid Arjmand; Mohammad Ali Sanjari; Hamid Reza Mokhtarinia; Morteza Asgari; Mohammad Parnianpour
Volume 7, Issue 4 , June 2013, , Pages 333-340
Abstract
Stability is important to prevent falling during occupational and daily living activities. Control parameters such as direction of motion and external load can affect stability pattern. The purpose of this paper was to evaluate the effect of the mentioned control parameters on stability. Time series ...
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Stability is important to prevent falling during occupational and daily living activities. Control parameters such as direction of motion and external load can affect stability pattern. The purpose of this paper was to evaluate the effect of the mentioned control parameters on stability. Time series of lumbar rotation angle in 19 healthy subjects were investigated. Each subject performed spine flexionextension in two different directions of symmetric (sagittal plane) and asymmetric (between sagittal and transverse planes), with two loading cases of 8 Kg weight and load free. To evaluate dynamic stability of repetitive movement, a nonlinear method of largest Lyapunov exponent has been used. After calculating maximum Lyapunov exponent from each of the experimental cases, results of analysis of variance showed a significant difference between symmetric and asymmetric directions (p=0.016). To interpret this result we can suggest higher recruitment of the internal and external oblique muscle groups and higher mechanical constraints in spine during asymmetric tasks. Mean comparison showed that movement in symmetric direction has more instability than the asymmetric case. Moreover, presence of load and interaction between direction and load did not significantly affect local dynamic stability.
Abolfazl Tabatabaei; Vali Derhami; Razieh Sheikhpour; Mohammad-Reza Pajoohan
Volume 13, Issue 4 , December 2019, , Pages 337-348
Abstract
Feature selection is a well-known preprocessing technique in machine learning, data mining and especially bioinformatics microarray analysis with a high-dimension, low-sample-size (HDLSS) data. The diagnosis of genes responsible for disease using microarray data is an important issue to promoting knowledge ...
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Feature selection is a well-known preprocessing technique in machine learning, data mining and especially bioinformatics microarray analysis with a high-dimension, low-sample-size (HDLSS) data. The diagnosis of genes responsible for disease using microarray data is an important issue to promoting knowledge about the mechanism of disease and improves the way of dealing with the disease. In feature selection methods based on information theory, which cover a wide range of feature selection methods, the concept of entropy is used to define criteria for relevance, redundancy and complementarity. In this paper, we propose a new relevancy criterion based on the concept of pure continuity rather than the concept of entropy. In the proposed method, to control and reduce redundancy, the relevancy between a feature and each class is separately examined, while in most of the filter methods the value of a feature is measured based on its relation to the entire class. This solution allows us to identify the most efficient features (genes) of each class separately, while identifying common features (genes) is also possible. Discretization is another challenge in some available techniques. Using a homomorphism transformation in proposed method avoids engaging with discretization complexities, while taking advantages of it. Seven types of cancer microarrays with three types of classification models (e.g. NB, KNN and SVM) are used to establish a comparison between the proposed method and other relevant methods. The results confirm the efficiency of the proposed method in the term of accuracy and number of selected genes as two parameters of classification.
Gait Analysis
Ghazaleh Soleimani; Mehran Emadi Andani; Hamid Reza Marateb; Fariba Bahrami
Volume 9, Issue 4 , February 2015, , Pages 361-374
Abstract
Walking is one of the most widely used movements affecting life quality. Therefore, the study of factors affecting human gait has always been an important issue. Walking speed, as a physical perturbation, affects the quality of human walking. The purpose of this study is to estimate the effects of walking ...
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Walking is one of the most widely used movements affecting life quality. Therefore, the study of factors affecting human gait has always been an important issue. Walking speed, as a physical perturbation, affects the quality of human walking. The purpose of this study is to estimate the effects of walking speed on the short-time gait parameters. Thirty-two healthy subjects(mean SD, age: 27.56 ± 20.4 years; body height: 158.19 ± 20.83 cm; body weight: 54.89 ± 20.59 kg;gender: 59% female)participated in this study.Kinetic, kinematic and electromyographic data were recorded at the following five walking speed categories: very slow, slow, medium, fast and very fast. The effect of speed on spatio-temporal parameters, muscle synergy space, walking smoothness, representation of joints displacement and the correlation between lower limb displacement and also correlation between muscles activation patterns were studied. Having being used physical perturbation, 46 predictors were extracted from one gait cycle information, some of which were proposed for the first time inthe literature for example size of muscle synergy, minimum angular jerk, lower limb contributions and skewness, kurtosis and curvature of joints movements . Using muscle synergies showed that increasing walking speed leads to increase the size of synergy space. It could be concluded that central nervous system tries to adopt more organaized strategy for recruiting muscles and remaining stable at fast speeds. Our results showed that, speed plays a crucial role in human gait characteristic. We can investigate our methods among more subjects and also patients with gait disorders. We can evaluate other indices like gait stability based on short-term data recording.
Biological Computer Modeling / Biological Computer Simulation
Mohammad Jazlaeiyan; Hadi Shahriar Shahhoseini
Volume 8, Issue 4 , February 2015, , Pages 371-383
Abstract
Human visual system operates superior than best machine vision systems in object recognition. So, researchers in machine vision and neuroscience try to model human visual system in order to employ it in machine. HMAX is one of the best operating models in this area. It is based on the function of brain ...
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Human visual system operates superior than best machine vision systems in object recognition. So, researchers in machine vision and neuroscience try to model human visual system in order to employ it in machine. HMAX is one of the best operating models in this area. It is based on the function of brain cells in the ventral stream of visual cortex and contains four computational layers. In the learning stage, many image partitions called image patches are extracted randomly with different sizes from training images. This random selection of image patches is one of the drawbacks of HMAX which decreases the performance and increases the computational complexity of the algorithm. In this paper, a novel patch selection from the set of random patches is proposed. In this method, using a recursive approach, optimal patches are selected from optimal features of training images by mutual information maximization feature selection. The performance of proposed algorithm in binary classification (existence or non-existence of objects in the images) is compared with HMAX and the superiority is proved.
Cognitive Biomedical Engineering
Elnaz Hamze; Zahra Bahmani Dehkordi; Mohammad Rostami
Volume 17, Issue 1 , May 2023, , Pages 31-40
Abstract
Working memory (WM) is an important cognitive function. Since WM capacity is limited, extensive research has been executed to improve it. Previous studies demonstrated that applying transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (DLPFC) enhances visual WM. ...
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Working memory (WM) is an important cognitive function. Since WM capacity is limited, extensive research has been executed to improve it. Previous studies demonstrated that applying transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (DLPFC) enhances visual WM. Capacity enhancement of WM has a significant effect on the pilot's efficiency. However, little is known about the auditory-verbal WM of Pilots. Therefore, the aim of this study is to evaluate the effects of tDCS over the left DLPFC on the WM capacity augmentation of pilots. The auditory-verbal WM stimuli comprise characters that are random numbers and alphabet letters. The stimulus is presented through the pilot's headset, and he has been persuaded to memorize the auditory stimulus and repeat the memorized characters. The auditory task is a set of 30 voices and is designed in 6 stages. The task starts from the easiest stage (4 characters) and continues with 2 increments of characters per stage to the most difficult stage (14 characters). The experiment was conducted under three conditions: baseline, sham, and anodal-tDCS. Before running the task, 2mA electrical stimulation with a duration of 30 seconds for the sham and 10 minutes for the anodal-tDCS conditions, was applied over the left DLPFC region of pilots. The performance measure is the number of correct remembered characters. Statistical hypotheses showed significant effects of anodal-tDCS in comparison to baseline condition as follows: %6.41 WM enhancement by considering all stages; and also improved performance around %12.20 in stage 4, %9.00 in stage 5, and %10.44 in stage 6 which are the most difficult stages. As a result, we found that 2mA anodal-tDCS over the left DLPFC can modulate WM capacity. The current study can be utilized to discover evidence of cognitive, behavioral, or neural mechanisms of WM and its application for human augmentation.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Amir Reza Asadi; Aboozar Ghaffari
Volume 16, Issue 4 , March 2023, , Pages 41-50
Abstract
One of the procedures for estimating fetal heart rate (FHR) is the use of an electrocardiogram (ECG). The ECG is a safe, inexpensive, and convenient method that can be used for remote monitoring, so maternal abdominal ECG recording (AECG) is used. The AECG signal, in addition to the fetal ECG (FECG), ...
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One of the procedures for estimating fetal heart rate (FHR) is the use of an electrocardiogram (ECG). The ECG is a safe, inexpensive, and convenient method that can be used for remote monitoring, so maternal abdominal ECG recording (AECG) is used. The AECG signal, in addition to the fetal ECG (FECG), includes the maternal ECG (MECG), maternal or fetal muscle activity, fetal brain activity, and noise, making it difficult to estimate the fetal heart rate based on the abdominal signal. In this study, the fetal heart rate is estimated from the single-channel AECG signal utilizing non-negative matrix factorization (NMF). In this method, the short-time Fourier transform (STFT) is used to obtain time-frequency information of the abdominal signal. Next, the NMF utilizes the STFT matrix as input. The rows of the non-negative matrix resulting from the NMF contain the content of maternal, fetal, and noise, which are used to detect R-peak and FHR. It performs well when MECG and FECG amplitudes are close together, which is one of the advantages of this method. The robustness and performance of the proposed algorithm have been compared with other state-of-the-art single-channel approaches, including deep learning models, on two databases, ADFECGDB and PCDB. Statistical analysis demonstrates that the proposed method is capable of estimating FHR and R-peak accurately. As a result, the proposed method is suitable for long-term fetal monitoring.
Tissue Engineering
Mohammad Haghpanahi; Mohammad Nikkhoo; Habibollah Peirovi
Volume 2, Issue 1 , June 2008, , Pages 47-56
Abstract
According to mechanobilogical studies as an infrastructure for tissue engineering researches, this paper presents a triphasic finite element modeling of intervertebral discs such a hydrated porous soft tissue. First, the governmental equations were derived on the basis of the laws of continuum mechanics. ...
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According to mechanobilogical studies as an infrastructure for tissue engineering researches, this paper presents a triphasic finite element modeling of intervertebral discs such a hydrated porous soft tissue. First, the governmental equations were derived on the basis of the laws of continuum mechanics. Then the standard Galerkin weighted residual method was used to form the finite element model. The implicit time integration schemes were applied to solve the nonlinear equations. The formulation accuracy and convergence for one dimensional case were examined with Simon's and Sun's analytical solutions and also Drost's experimental Data. It was shown that the mathematical model is in excellent agreement and has the capability to simulate the intervertebral disc response under different types of mechanical and electrochemical loading conditions. Finally, to have a short review of the capability of the model, a homogenous two dimensional version of the model was applied to simulate the response of a simple sagittal slice of the intervertebral disc.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Sorour Behbahani; Ali Motie Nasrabadi
Volume 4, Issue 1 , June 2010, , Pages 53-64
Abstract
The analysis of EEG signals plays an important role in a wide range of applications, such as psychotropic drug research, sleep studies, seizure detection and hypnosis processing. From years ago hypnosis was known as a method to help the patients in different fields such as reduction of stress, leaving ...
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The analysis of EEG signals plays an important role in a wide range of applications, such as psychotropic drug research, sleep studies, seizure detection and hypnosis processing. From years ago hypnosis was known as a method to help the patients in different fields such as reduction of stress, leaving bad habits, pain control and etc. EEG signals during pure hypnosis would differ from those recorded in the normal no hypnotic conditions. There are several methods for analyzing the EEG signal and similarity index method is one of the famous methods in this branch. In this paper the features of EEG signal of three groups of people with different hypnotizability during hypnosis (Fractal, Wavelet Entropy, Frequency Bands) from left-right and frontal-back lobes were extracted and analyzed using Fuzzy Similarity Index Method to find whether there are any significant relations between the function of these hemispheres and hypnotizability degree. Finally after detecting the significancy, we used the selected features were used to classify the subjects into three groups of hypnotizability. The best classification accuracy was obtained 94% (for two classes of features 1. entropy, Higuchi, high frequency, 2. energy and entropy) and the lowest was 87.5% (for entropy, Higuchi and low frequency features).
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Mohammad Reza Nourouzi; Mohammad Javad Yazdanpanah
Volume 1, Issue 1 , June 2007, , Pages 53-62
Abstract
Ventricular Fibrillation (VF) is a dangerous abnormality in the heart activity. During the VF, well known shape of electrocardiogram (ECG) signal changes to a pseudo-noise waveform. Recent researches have depicted that VF is not a noisy signal. The characteristics of VF and chaotic signals are the same. ...
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Ventricular Fibrillation (VF) is a dangerous abnormality in the heart activity. During the VF, well known shape of electrocardiogram (ECG) signal changes to a pseudo-noise waveform. Recent researches have depicted that VF is not a noisy signal. The characteristics of VF and chaotic signals are the same. In this research, these characteristics were studied and used for discriminating the VF signal from the other electrocardiogram signals. Three types of electrocardiogram signals including VF, Tachycardia and Normal ECG were used for training and testing a back propagation neural network. We used these signals in three stages. At the first stage, the power spectrum of signals was used for training and testing the neural network. Time Series signals were used in the second stage. The result of the first experience was better than the second. At the third stage, we used surrogate technique to enrich the training signals in the time domain. The surrogate technique is a method which has been used in the chaotic systems. By using these new generated signals for training the neural network, the results of classification were extremely improved. Furthermore, the results of simulations showed that the chaotic dynamic of VF signal is a time dependant one.
Biomedical Image Processing / Medical Image Processing
Mohammad Aboonajmi; Asadollah Akram; Seyed Kamaloddin Setarehdan; Ali Rajabipour
Volume 3, Issue 1 , June 2009, , Pages 55-65
Abstract
Ultrasound is a rapidly growing tool in the field of research, which shows an increasing use in the food industry for both analysis and modification of food products. Quality assessment of agricultural material has an important role in modern agriculture. This study demonstrates the possibility of non-destructive ...
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Ultrasound is a rapidly growing tool in the field of research, which shows an increasing use in the food industry for both analysis and modification of food products. Quality assessment of agricultural material has an important role in modern agriculture. This study demonstrates the possibility of non-destructive prediction of the main quality indices of the commercial eggs by processing a short ultrasound burst passing through the egg material and calculating the ultrasound phase velocity. For this purpose a set of three hundred samples of commercial eggs (Boris Brown, 33 weeks age) from the first day of egg lying were purchased from a farm and classified in two groups. The first group was kept in the room temperature (22-25°C) while the second group was kept within the refrigerator (4-5°C). 25 eggs were picked every week from each groups (room and refrigerator) were first subjected to the nondestructive ultrasound test at room temperature. Each day, the ultrasound signal is recorded from the eggs first. Then, immediately after that, the air cell, the thick albumen heights, the Haugh unit and the yolk index of the eggs were also determined destructively for comparison purposes. Significant differences at 5% level between the means of the destructive analysis at different days of storage of the eggs were found using ANOVA. Both the Haugh unit and yolk index decreased by time over 5 weeks in storage at room and refrigerator while the air cell height increased. The lower is the Haugh unit for the eggs in the refrigerator the lower is the phase velocity (1573 m/s at first day compared to 1540 m/s after 3 weeks). Similar changes of the phase velocity are found for the eggs in the room temperature (1571 m/s at first day compared to 1514 m/s after 3 weeks).
Biological Computer Modeling / Biological Computer Simulation
Sajad Shafiekhani; Amin Mashayekhi Shams; Seyed Yashar Banihashem; Nematollah Gheibi; Amir Homayoun Jafari
Volume 14, Issue 1 , May 2020, , Pages 55-67
Abstract
According to cancer’s global statistics, there will be 27.5 million new cases of cancer each year by 2040, therefore, it is crucial to achieve a deeper understanding of the cancer progression mechanisems and immune system functions in response to it. Nowadays, computational models are widely used ...
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According to cancer’s global statistics, there will be 27.5 million new cases of cancer each year by 2040, therefore, it is crucial to achieve a deeper understanding of the cancer progression mechanisems and immune system functions in response to it. Nowadays, computational models are widely used to capture dynamics of the tumor- immune system (TIS). The proposed model on this manuscript is on the basis of the ordinary differential equations which mechanistically models the interactions of tumor cells, CTLs, NKs and MDSCs. CTLs and NK cells are the most important cells of adaptive and innate immune system, respectively that encounter with tumor cells, while MDSCs as immature immune cells suppress the immune responses in the inflammatory environments. Due to the error of the in-vivo/in-vitro experiments, vagueness, imprecise information, incomplete data and natural variability of the tumor-immune system emerges between different individuals, the kinetic parameters of computational models are uncertain that this uncertainty can be captured by fuzzy sets. Hence, we assign fuzzy numbers with triangular membership functions instead of crisp numbers to some kinetic parameters of the tumor–immune system model. In fact, the uncertainty in the kinetic parameters of the ordinary differential equations affects the dynamic of the system species. In this essay, for the first time, a fuzzy number has been used to model the uncertainty of the parameters of the ODE model. Our data reveals that increasing/decreasing the uncertainty region of the model's fuzzy parameters increases/decreases the uncertainty region of dynamics of species. Furtheremore, the simulations of the model in the crisp setting of parameters show that the repition of 5-FU treatment for inhibition of MDSCs dramatically inhibits tumor cells and eradicate tumor.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Ali Khadem; Gholam Ali Hossein-Zadeh
Volume 6, Issue 1 , June 2012, , Pages 57-69
Abstract
Exploring the causal (delayed) brain relations is an important topic in the Neuroscience. The traditional estimators of brain causal (delayed) relations are mainly model-based and put restrictive assumptions on the brain dynamics. In the recent years, some nonparametric measures have been introduced ...
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Exploring the causal (delayed) brain relations is an important topic in the Neuroscience. The traditional estimators of brain causal (delayed) relations are mainly model-based and put restrictive assumptions on the brain dynamics. In the recent years, some nonparametric measures have been introduced to solve this problem. Among them, the most important one is Transfer Entropy (TE) which is based on the information theory and Conditional Mutual Information concept. However, in the presence of significant instantaneous relations that are observed extensively in the brain functional datasets, TE may estimate the causal (delayed) relations inaccurately. In this paper, two information theoretic based measures called Instantaneous Interaction (II) and Modified Transfer entropy (MTE) are introduced to estimate the instantaneous and causal (delayed) brain relations, respectively. MTE is used instead of TE whenever II is significant. These measures are evaluated on 3 simulated models and eyes-closed resting state EEG data. The simulation results show high ability of II to estimate the linear and nonlinear instantaneous relations. Also, based on the simulation results MTE outperforms TE to estimate causal (delayed) relations in presence of significant instantaneous relations (significant II). For the real EEG data, II detects a significant instantaneous relation between Posterior and Frontal EEG channels. Also MTE detects the information flow from Posterior EEG channels to Frontal ones more significantly than TE does. So in presence of significant instantaneous relations in the real EEG data, MTE outperforms TE.
Bioheat Transfer
Mohammad Shams Kolahi; Ataollah Hashemi
Volume 5, Issue 1 , June 2011, , Pages 57-66
Abstract
Recent technological and industrial advances have increased the number of skin burns due to human body exposure to heat in a fire or hot and mechanized environment. In addition, hot environment can produce a strain on a human body leading to discomfort and heat stress and even death. In hot summer days, ...
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Recent technological and industrial advances have increased the number of skin burns due to human body exposure to heat in a fire or hot and mechanized environment. In addition, hot environment can produce a strain on a human body leading to discomfort and heat stress and even death. In hot summer days, many people suffer from heat stroke, dehydration and loss of body fluid. Therefore, the subject of studying thermal energy transport in living tissues is useful for assessing skin burns accurately, better understanding the thermoregulatory system of the body and for developing thermal protection standards. In a hot environment, the most important factor to control the body temperature is evaporation. Accordingly, this study solves one dimensional Pennes’ bio-heat equation by means of backward finite difference formulation. Physical and physiological factors taken into account are: sweat secretion, capillary blood circulation (perfusion), metabolic heat, heat and water exchange with the environment through convection and evaporation. Initially, the model is validated using the work of Zhao et al. Then, the evaporation term is added to the model to study the effect of ambient temperature variation on skin tissue temperature. The results show that thermal disease such as hyperthermia can be expected if uncovered skin is held for a specific time at hot environment. It is observed that increasing ambient temperature causes a shift in the location of the maximum temperature toward the surface of the skin, i.e., the maximum temperature occurs at the depth of about 9 and 7.6 mm of skin surface for ambient temperature of 50 and 60°C, respectively.
Neuro-Muscular Engineering
Amir Homayoun Jafari; Seyed Mohammad Reza Hashemi Golpayegani; Farzad Towhidkhah; Ali Fallah
Volume -2, Issue 1 , July 2005, , Pages 57-70
Abstract
A hierarchical structure model with three levels is presented for modeling motor control in skill movements. At each level, based on accuracy and quality of control, a specific controller is activated. At first level, control concepts are qualitative. The duty of the first level is to provide stability ...
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A hierarchical structure model with three levels is presented for modeling motor control in skill movements. At each level, based on accuracy and quality of control, a specific controller is activated. At first level, control concepts are qualitative. The duty of the first level is to provide stability of system, based on the received qualitative information from second level such as the decrement or increment of error. A self-organized controller at first level is used to generate qualitative control commands, and it plays an encouragement-punishment role to keep the stability of system by sending discrete commands to the second level. This controller only contributes at control action when the controller of second level can not preserve stability individually. At second level, control concepts are quantitative. The duty of the second level is adaptation and control of system accurately. The received information at this level generally comes from sensory and visual feedbacks, and it includes more accurate concepts of control action - like the amount of movement error. A model based on the predictive controller at second level generates quantitative control commands and indeed, determines trajectory of movement accurately. A fuzzy switch combines the control commands of first and second levels, based on the sliding mode strategy, to provide a robust control. At third level, this command is interpreted and then is applied to the involved muscles in movement. The received information at this level is generally the contribution of muscles in performing movement and the effects of environment on the movement, which comes from sensory feedbacks. The presented model with this hierarchical structure has a proper ability to control and keep the stability of system. The simulation results confirm this subject.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Masoumeh Rahimi; Mohammad Hasan Moradi; Farnaz Ghassemi
Volume 10, Issue 1 , May 2016, , Pages 59-68
Abstract
The aim of this paper is to study brain effective connectivity based on directed transform function (DTF) using granger causality method. This connectivity was calculated for recorded data in different states of attention and consciousness, forming four different classes: attention-consciousness, attention-unconsciousness, ...
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The aim of this paper is to study brain effective connectivity based on directed transform function (DTF) using granger causality method. This connectivity was calculated for recorded data in different states of attention and consciousness, forming four different classes: attention-consciousness, attention-unconsciousness, inattention-consciousness, and inattention-unconsciousness. Some common indices were extracted and calculated from the connectivity matrices. Indices of these four classes were compared to see whether there is a significant difference among them or not. The Multivariate Autoregressive (MVAR) model was used to obtain the linear causal relations between channels. Furthermore, signals were divided into four frequency bands for more accurate investigation, and the existence of significant difference was investigated with two-way repeated measures test. Results indicated that and among twelve indices could show a significant difference (p<0.05) in five states out of six possible states. The only state that no feature was able to show a meaningful difference was inattention-consciousness, and inattention-unconsciousness.
Biological Computer Modeling / Biological Computer Simulation
Mohammad Reza Khodabakhshi; Amir Hossein Davaie Markazi
Volume 11, Issue 1 , May 2017, , Pages 63-81
Abstract
Nowadays, with technological advancements and increasing computing power, the use of mathematical models to describe the functioning of the brain in normal and abnormal manners, especially the study of the formation causes and methods of controlling and treating some nervous system diseases, such as ...
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Nowadays, with technological advancements and increasing computing power, the use of mathematical models to describe the functioning of the brain in normal and abnormal manners, especially the study of the formation causes and methods of controlling and treating some nervous system diseases, such as epilepsy, have become widespread and many models have been developed to simulate patterns appearing in the brain signals of these patients. One of the most commonly used types of modeling is neural mass models such as the Jansen-Rit model that those can simulate some of the essential brain patterns and rhythms that appear in the brain recorded signals. Therefore, in this paper, we have tried to provide a complete dynamical analysis of the Jansen-Rit model. To analyze this model, first, the equations of the model have been changed so that the output of the model be one of the system states variables. Then, the new equations have been nondimensionalized by defining a biological parameter (proportion of inhibition to excitation in neural populations of the model). In the following, the bifurcation diagram of the dimensionless model has been plotted with respect to nondimensional input and inhibition to excitation proportion parameters (codimension-two bifurcation) and the dynamical behavior of the system, such as bifurcations, periods and frequency of the limit cycles and time responses, have been investigated. Further, we have discussed two significant behaviors in this model, spike-and-wave discharges (SWDs) and alpha rhythms. In the present paper, we have been shown how these models can describe complex disease such as epilepsy and have been mentioned dynamical mechanism underlying transition from a normal state (background activity) to an abnormal situation (epileptic seizures). The innovations of this study one can be the definition of the new meaningful and significant biological parameter in the dimensionless model that all dynamical analysis are based on it. Also, some bifurcations and, consequently, some of the behaviors observed in the model are for the first time reported. Moreover, this new parameter contains two primary model parameters and then the effect of three parameters simultaneously in the system behavior has been investigated.
Orthopedic Biomechanics
Javad Mortazavi; Farzam Farahmand; Saeed Behzadipour; Ali Yeganeh
Volume 12, Issue 1 , June 2018, , Pages 63-74
Abstract
Intramedullary nailing is a common technique for treatment of femoral shaft fractures. Nail deformation after insertion into the bone, makes the distal hole locking a challenging task for the surgeon. The proximally mounted targeting systems for locating the position of the distal hole become ineffective ...
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Intramedullary nailing is a common technique for treatment of femoral shaft fractures. Nail deformation after insertion into the bone, makes the distal hole locking a challenging task for the surgeon. The proximally mounted targeting systems for locating the position of the distal hole become ineffective due to the nail deformation. The previous image-based techniques have often considered the shape of the distal end of the nail only to find the position and direction of the distal hole. The purpose of this study was to evaluate the hypothesis of possibility of locating the position of the distal hole using mechanical modeling and radiography data simultaneously. In the proposed method, according to the nail geometry (length to diameter ratio between 25 and 50), an Euler-Bernoulli beam model is used to simulate the mechanical behavior of the nail and calculate its deformation pattern. Then, by registering the deformation pattern with the sagittal radiography image of the nail, using iterative closest point algorithm, the nail deformation and the position of the distal hole are predicted. In order to evaluate the research hypothesis, a number of experiments were performed on five cadaveric femurs and the predicted and actual positions of the distal hole were compared. Results indicated that by using mechanical modeling and the imaging data of the nail curvature, the position of the distal hole could be predicted with a mean error of 0.84 mm and a maximum error of 1.3 mm. It is expected that by combining the proposed method with the image-based techniques, which make use of the shape data of the hole, a sub-millimeter error in locating the distal hole could be achieved in future.
Biomedical Imaging / Medical Imaging
Elham Mohammadi; Abbas Nasiraei Moghaddam
Volume 16, Issue 1 , May 2022, , Pages 63-74
Abstract
Real-time MRI using highly undersampled radial acquisition can be used for dynamic assessments of the heart. The main challenges, however, are the presence of severe undersampling artifacts in the periphery of the images. In this study, to improve the visual quality of the final real-time images, a new ...
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Real-time MRI using highly undersampled radial acquisition can be used for dynamic assessments of the heart. The main challenges, however, are the presence of severe undersampling artifacts in the periphery of the images. In this study, to improve the visual quality of the final real-time images, a new method for the acquisition of successive frames based on a radial trajectory with the turned arrangement is presented. Accordingly, by combining the information obtained from successive frames, it is possible to reconstruct images with high and low spatial resolution. In the proposed method, specifically due to the use of the Polar Fourier Transform reconstruction method, reconstructed images with two different resolutions can be combined to reduce the visual effects of undersampling artifacts. In this paper, the proposed method has been used especially for the real-time radially tagged images to increase the efficiency and accuracy of measuring left ventricular rotation motion. According to the simulation results, the structural similarity measure is improved from 0.6 to 0.8. Real-time imaging with a time resolution of 46 ms of healthy individuals also shows that while the temporal resolution of the rotational information is well preserved, the visual quality of images is improved.