Publications by authors named "Amir Homayoun Jafari"

27 Publications

  • Page 1 of 1

Toward New Modalities in VEP-Based BCI Applications Using Dynamical Stimuli: Introducing Quasi-Periodic and Chaotic VEP-Based BCI.

Front Neurosci 2020 17;14:534619. Epub 2020 Nov 17.

Department of Medical Physics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Visual evoked potentials (VEPs) to periodic stimuli are commonly used in brain computer interfaces for their favorable properties such as high target identification accuracy, less training time, and low surrounding target interference. Conventional periodic stimuli can lead to subjective visual fatigue due to continuous and high contrast stimulation. In this study, we compared quasi-periodic and chaotic complex stimuli to common periodic stimuli for use with VEP-based brain computer interfaces (BCIs). Canonical correlation analysis (CCA) and coherence methods were used to evaluate the performance of the three stimulus groups. Subjective fatigue caused by the presented stimuli was evaluated by the Visual Analogue Scale (VAS). Using CCA with the M2 template approach, target identification accuracy was highest for the chaotic stimuli ( = 86.8, = 1.8) compared to the quasi-periodic ( = 78.1, = 2.6, = 0.008) and periodic ( = 64.3, = 1.9, = 0.0001) stimulus groups. The evaluation of fatigue rates revealed that the chaotic stimuli caused less fatigue compared to the quasi-periodic ( = 0.001) and periodic ( = 0.0001) stimulus groups. In addition, the quasi-periodic stimuli led to lower fatigue rates compared to the periodic stimuli ( = 0.011). We conclude that the target identification results were better for the chaotic group compared to the other two stimulus groups with CCA. In addition, the chaotic stimuli led to a less subjective visual fatigue compared to the periodic and quasi-periodic stimuli and can be suitable for designing new comfortable VEP-based BCIs.
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http://dx.doi.org/10.3389/fnins.2020.534619DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718037PMC
November 2020

Extended Robust Boolean Network of Budding Yeast Cell Cycle.

J Med Signals Sens 2020 Apr-Jun;10(2):94-104. Epub 2020 Apr 25.

Department of Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Background: How to explore the dynamics of transition probabilities between phases of budding yeast cell cycle (BYCC) network based on the dynamics of protein activities that control this network? How to identify the robust structure of protein interactions of BYCC Boolean network (BN)? Budding yeast allows scientists to put experiments into effect in order to discover the intracellular cell cycle regulating structures which are well simulated by mathematical modeling.

Methods: We extended an available deterministic BN of proteins responsible for the cell cycle to a Markov chain model containing apoptosis besides G1, S, G2, M, and stationary G1. Using genetic algorithm (GA), we estimated the kinetic parameters of the extended BN model so that the subsequent transition probabilities derived using Markov chain model of cell states as normal cell cycle becomes the maximum while the structure of chemical interactions of extended BN of cell cycle becomes more stable.

Results: Using kinetic parameters optimized by GA, the probability of the subsequent transitions between cell cycle phases is maximized. The relative basin size of stationary G1 increased from 86% to 96.48% while the number of attractors decreased from 7 in the original model to 5 in the extended one. Hence, an increase in the robustness of the system has been achieved.

Conclusion: The structure of interacting proteins in cell cycle network affects its robustness and probabilities of transitions between different cell cycle phases. Markov chain and BN are good approaches to study the stability and dynamics of the cell cycle network.
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http://dx.doi.org/10.4103/jmss.JMSS_40_19DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359953PMC
April 2020

Computer-aided classifying and characterizing of methamphetamine use disorder using resting-state EEG.

Cogn Neurodyn 2019 Dec 7;13(6):519-530. Epub 2019 Aug 7.

5Iranian Center of Neurological Research, Neuroscience Institute, Tehran University of Medical Sciences (TUMS), Tehran, Iran.

Methamphetamine (meth) is potently addictive and is closely linked to high crime rates in the world. Since meth withdrawal is very painful and difficult, most abusers relapse to abuse in traditional treatments. Therefore, developing accurate data-driven methods based on brain functional connectivity could be helpful in classifying and characterizing the neural features of meth dependence to optimize the treatments. Accordingly, in this study, computation of functional connectivity using resting-state EEG was used to classify meth dependence. Firstly, brain functional connectivity networks (FCNs) of 36 meth dependent individuals and 24 normal controls were constructed by weighted phase lag index, in six frequency bands: delta (1-4 Hz), theta (4-8 Hz), alpha (8-15 Hz), beta (15-30 Hz), gamma (30-45 Hz) and wideband (1-45 Hz).Then, significant differences in graph metrics and connectivity values of the FCNs were used to distinguish the two groups. Support vector machine classifier had the best performance with 93% accuracy, 100% sensitivity, 83% specificity and 0.94 F-score for differentiating between MDIs and NCs. The best performance yielded when selected features were the combination of connectivity values and graph metrics in the beta frequency band.
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http://dx.doi.org/10.1007/s11571-019-09550-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6825232PMC
December 2019

An Agent-based Model for Investigating the Effect of Myeloid-Derived Suppressor Cells and its Depletion on Tumor Immune Surveillance.

J Med Signals Sens 2019 Jan-Mar;9(1):15-23

Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Background: To predict the behavior of biological systems, mathematical models of biological systems have been shown to be useful. In particular, mathematical models of tumor-immune system interactions have demonstrated promising results in prediction of different behaviors of tumor against the immune system.

Methods: This study aimed at the introduction of a new model of tumor-immune system interaction, which includes tumor and immune cells as well as myeloid-derived suppressor cells (MDSCs). MDSCs are immune suppressor cells that help the tumor cells to escape the immune system. The structure of this model is agent-based which makes possible to investigate each component as a separate agent. Moreover, in this model, the effect of low dose 5-fluorouracil (5-FU) on MDSCs depletion was considered.

Results: Based on the findings of this study, MDSCs had suppressive effect on increment of immune cell number which consequently result in tumor cells escape the immune cells. It has also been demonstrated that low-dose 5-FU could help immune system eliminate the tumor cells through MDSCs depletion.

Conclusion: Using this new agent-based model, multiple injection of low-dose 5-FU could eliminate MDSCs and therefore might have the potential to be considered in treatment of cancers.
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http://dx.doi.org/10.4103/jmss.JMSS_33_18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6419563PMC
April 2019

Introducing chaotic codes for the modulation of code modulated visual evoked potentials (c-VEP) in normal adults for visual fatigue reduction.

PLoS One 2019 6;14(3):e0213197. Epub 2019 Mar 6.

Medical Physics & Biomedical Engineering Department, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Code modulated Visual Evoked Potentials (c-VEP) based BCI studies usually employ m-sequences as a modulating codes for their broadband spectrum and correlation property. However, subjective fatigue of the presented codes has been a problem. In this study, we introduce chaotic codes containing broadband spectrum and similar correlation property. We examined whether the introduced chaotic codes could be decoded from EEG signals and also compared the subjective fatigue level with m-sequence codes in normal subjects. We generated chaotic code from one-dimensional logistic map and used it with conventional 31-bit m-sequence code. In a c-VEP based study in normal subjects (n = 44, 21 females) we presented these codes visually and recorded EEG signals from the corresponding codes for their four lagged versions. Canonical correlation analysis (CCA) and spatiotemporal beamforming (STB) methods were used for target identification and comparison of responses. Additionally, we compared the subjective self-declared fatigue using VAS caused by presented m-sequence and chaotic codes. The introduced chaotic code was decoded from EEG responses with CCA and STB methods. The maximum total accuracy values of 93.6 ± 11.9% and 94 ± 14.4% were achieved with STB method for chaotic and m-sequence codes for all subjects respectively. The achieved accuracies in all subjects were not significantly different in m-sequence and chaotic codes. There was significant reduction in subjective fatigue caused by chaotic codes compared to the m-sequence codes. Both m-sequence and chaotic codes were similar in their accuracies as evaluated by CCA and STB methods. The chaotic codes significantly reduced subjective fatigue compared to the m-sequence codes.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0213197PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402685PMC
December 2019

A Hybrid Multilayer Filtering Approach for Thyroid Nodule Segmentation on Ultrasound Images.

J Ultrasound Med 2019 Mar 31;38(3):629-640. Epub 2018 Aug 31.

Department of Medical Physics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Objectives: Speckle noise is the main factor that degrades ultrasound image contrast and segmentation failure. Determining an effective filter can reduce speckle noise and improve segmentation performances. The aim of this study was to define a useful filter to improve the segmentation outcome.

Methods: Twelve filters, including median, hybrid median (Hmed), Fourier Butterworth, Fourier ideal, wavelet (Wlet), homomorphic Fourier Butterworth, homomorphic Fourier ideal, homomorphic wavelet (Hmp_Wlet), frost, anisotropic diffusion, probabilistic patch-based (PPB), and homogeneous area filters, were used to find the best filter(s) to prepare thyroid nodule segmentation. A receiver operating characteristic (ROC) analysis was used for filter evaluation in the nodule segmentation process. Accordingly, 10 morphologic parameters were measured from segmented regions to find the best parameters that predict the segmentation performance.

Results: The best segmentation performance was reached by using 4 hybrid filters that mainly contain contrast-limited adaptive histogram equalization, Wlet, Hmed, Hmp_Wlet, and PPB filters. The area under the ROC curve for these filters ranged from 0.900 to 0.943 in comparison with the original image, with an area under the curve of 0.685. From 10 morphologic parameters, the area, convex area, equivalent diameter, solidity, and extent can evaluate segmentation performance.

Conclusions: Hybrid filters that contain contrast-limited adaptive histogram equalization, Wlet, Hmed, Hmp_Wlet, and PPB filters have a high potential to provide good conditions for thyroid nodule segmentation in ultrasound images. In addition to an ROC analysis, morphometry of a segmented region can be used to evaluate segmentation performances.
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http://dx.doi.org/10.1002/jum.14731DOI Listing
March 2019

Predictive quantitative sonographic features on classification of hot and cold thyroid nodules.

Eur J Radiol 2018 Apr 16;101:170-177. Epub 2018 Feb 16.

Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran; Department of Nuclear Medicine, Rajaei Cardiovascular, Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran. Electronic address:

Purpose: This study investigated the potentiality of ultrasound imaging to classify hot and cold thyroid nodules on the basis of textural and morphological analysis.

Methods: In this research, 42 hypo (hot) and 42 hyper-function (cold) thyroid nodules were evaluated through the proposed method of computer aided diagnosis (CAD) system. To discover the difference between hot and cold nodules, 49 sonographic features (9 morphological, 40 textural) were extracted. A support vector machine classifier was utilized for the classification of LNs based on their extracted features.

Results: In the training set data, a combination of morphological and textural features represented the best performance with area under the receiver operating characteristic curve (AUC) of 0.992. Upon testing the data set, the proposed model could classify the hot and cold thyroid nodules with an AUC of 0.948.

Conclusions: CAD method based on textural and morphological features is capable of distinguishing between hot from cold nodules via 2-Dimensional sonography. Therefore, it can be used as a supplementary technique in daily clinical practices to improve the radiologists' understanding of conventional ultrasound imaging for nodules characterization.
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http://dx.doi.org/10.1016/j.ejrad.2018.02.010DOI Listing
April 2018

Analysis of Resting-State fMRI Topological Graph Theory Properties in Methamphetamine Drug Users Applying Box-Counting Fractal Dimension.

Basic Clin Neurosci 2017 Sep-Oct;8(5):371-385

Department of Neuro-Imaging and Analysis, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran.

Introduction: Graph theoretical analysis of functional Magnetic Resonance Imaging (fMRI) data has provided new measures of mapping human brain in vivo. Of all methods to measure the functional connectivity between regions, Linear Correlation (LC) calculation of activity time series of the brain regions as a linear measure is considered the most ubiquitous one. The strength of the dependence obligatory for graph construction and analysis is consistently underestimated by LC, because not all the bivariate distributions, but only the marginals are Gaussian. In a number of studies, Mutual Information (MI) has been employed, as a similarity measure between each two time series of the brain regions, a pure nonlinear measure. Owing to the complex fractal organization of the brain indicating self-similarity, more information on the brain can be revealed by fMRI Fractal Dimension (FD) analysis.

Methods: In the present paper, Box-Counting Fractal Dimension (BCFD) is introduced for graph theoretical analysis of fMRI data in 17 methamphetamine drug users and 18 normal controls. Then, BCFD performance was evaluated compared to those of LC and MI methods. Moreover, the global topological graph properties of the brain networks inclusive of global efficiency, clustering coefficient and characteristic path length in addict subjects were investigated too.

Results: Compared to normal subjects by using statistical tests (P<0.05), topological graph properties were postulated to be disrupted significantly during the resting-state fMRI.

Conclusion: Based on the results, analyzing the graph topological properties (representing the brain networks) based on BCFD is a more reliable method than LC and MI.
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http://dx.doi.org/10.18869/nirp.bcn.8.5.371DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5691169PMC
November 2017

Changes in Effective Connectivity Network Patterns in Drug Abusers, Treated With Different Methods.

Basic Clin Neurosci 2017 Jul-Aug;8(4):285-298

Department of Nouroimaging and Analysis, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran.

Introduction: Various treatment methods for drug abusers will result in different success rates. This is partly due to different neural assumptions and partly due to various rate of relapse in abusers because of different circumstances. Investigating the brain activation networks of treated subjects can reveal the hidden mechanisms of the therapeutic methods.

Methods: We studied three groups of subjects: heroin abusers treated with abstinent based therapy (ABT) method, heroin abusers treated with Methadone Maintenance Therapy (MMT) method, and a control group. They were all scanned with functional magnetic resonance imaging (fMRI), using a 6-block task, where each block consisted of the rest-craving-rest-neutral sequence. Using the dynamic causal modeling (DCM) algorithm, brain effective connectivity network (caused by the drug craving stimulation) was quantified for all groups. In this regard, 4 brain areas were selected for this analysis based on previous findings: ventromedial prefrontal cortex (VMPFC), dorsolateral prefrontal cortex (DLPFC), amygdala, and ventral striatum.

Results: Our results indicated that the control subjects did not show significant brain activations after craving stimulations, but the two other groups showed significant brain activations in all 4 regions. In addition, VMPFC showed higher activations in the ABT group compared to the MMT group. The effective connectivity network suggested that the control subjects did not have any direct input from drug-related cue indices, while the other two groups showed reactions to these cues. Also, VMPFC displayed an important role in ABT group. In encountering the craving pictures, MMT subjects manifest a very simple mechanism compared to other groups.

Conclusion: This study revealed an activation network similar to the emotional and inhibitory control networks observed in drug abusers in previous works. The results of DCM analysis also support the regulatory role of frontal regions on bottom regions. Furthermore, this study demonstrates the different effective connectivity patterns after drug abuse treatment and in this way helps the experts in the field.
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http://dx.doi.org/10.18869/nirp.bcn.8.4.285DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5683686PMC
November 2017

Design of an optimum Poincaré plane for extracting meaningful samples from EEG signals.

Australas Phys Eng Sci Med 2018 Mar 16;41(1):13-20. Epub 2017 Nov 16.

Medical Physics & Biomedical Engineering Department, Tehran University of Medical Sciences (TUMS), Tehran, Iran.

Biosignals are considered as important sources of data for diagnosing and detecting abnormalities, and modeling dynamics in the body. These signals are usually analyzed using features taken from time and frequency domain. In theory' these dynamics can also be analyzed utilizing Poincaré plane that intersects system's trajectory. However' selecting an appropriate Poincaré plane is a crucial part of extracting best Poincaré samples. There is no unique way to choose a Poincaré plane' because it is highly dependent to the system dynamics. In this study, a new algorithm is introduced that automatically selects an optimum Poincaré plane able to transfer maximum information from EEG time series to a set of Poincaré samples. In this algorithm' EEG time series are first embedded; then a parametric Poincaré plane is designed and finally the parameters of the plane are optimized using genetic algorithm. The presented algorithm is tested on EEG signals and the optimum Poincaré plane is obtained with more than 99% data information transferred. Results are compared with some typical method of creating Poinare samples and showed that the transferred information using with this method is higher. The generated samples can be used for feature extraction and further analysis.
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http://dx.doi.org/10.1007/s13246-017-0599-2DOI Listing
March 2018

Prediction of epileptic seizures from EEG using analysis of ictal rules on Poincaré plane.

Comput Methods Programs Biomed 2017 Jul 6;145:11-22. Epub 2017 Apr 6.

Medical Physics & Biomedical Engineering Department, School of Medicine, Tehran University of Medical Sciences., Tehran, Iran. Electronic address:

Background And Objective: Epilepsy is a neurological disorder that causes recurrent and abrupt seizures which makes the patients insecure. Predicting seizures can reduce the burdens of this disorder.

Methods: A new approach in seizure prediction is presented that includes a novel technique in feature extraction from EEG. The algorithm firsts creates an embedding space from EEG time series. Then it takes samples with most of the information using an optimized and data specific Poincare plane. In order to quantify small dynamics on the Poincare plane, based on the order of locations of Poincaré samples in the sequence, 64 fuzzy rules in each channel are defined. Features are extracted based on the frequency distribution of these fuzzy rules in each minute. Then features with higher variance are selected as ictal features and again reduced using PCA. Finally, in order to evaluate how these innovative features can increase the performance of the seizure prediction algorithm, the transition from interictal to preictal state is scored utilizing SVM.

Results: The algorithm is tested on 460 h of EEG from 19 patients of Freiburg dataset who had at least 3 seizures. Considering maximum Seizure Prediction Horizon of 42 minutes, average sensitivity was 91.8 - 96.6% and average false prediction rate was 0.05 - 0.08/h.

Conclusions: The presented algorithm shows a better performance and more robustness compare to most of existing methods, and shows power in extracting optimal features from EEG.
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http://dx.doi.org/10.1016/j.cmpb.2017.04.001DOI Listing
July 2017

Changes in Back Compressive Force When Measuring Maximum Acceptable Weight of Lift in Iranian Male Students.

Iran J Public Health 2016 Sep;45(9):1199-1207

Medical Physics and Biomedical Engineering Department, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Background: Low back pain caused by work, ranked the second after cardiovascular diseases, are among the most common reasons of patients' referral to the physicians in Iran. This study aimed to determine the changes in back compressive force when measuring maximum acceptable weight of lift in Iranian male students.

Methods: This experimental study was conducted in 2015 on 15 young male students were recruited from Tehran University of Medical Science. Each participant performed 18 different lifting tasks involving three lifting frequencies, with three lifting heights, and two box sizes. Each set of experiments was conducted during the 20 min work period using free-style lifting technique. The back compressive force evaluated with hand-calculation back compressive force method. Finally, Pearson correlation test, analysis of variance (ANOVA) and t-test were used for data analysis.

Results: The mean of back compressive force (BCF) for the small and large boxes at a frequency of 1lift/min at heights of F - K height, were 1001.02 (±86.74), 1210.57 (±93.77) Ib, respectively. There was a significant difference between mean BCF in terms of frequencies of lifts (=0.02). The result revealed significant difference between frequencies of 1 lift/min and 6.67 lift/min (=0.01). There was a significant difference between mean BCF in terms of the sizes of the two boxes (=0.001). There was a significant relationship between the BCF and maximum acceptable weight of lift in all test conditions (=0.001).

Conclusion: BCF is affected by box size, lifting frequency and weight of load.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5149474PMC
September 2016

Non-auditory Effect of Noise Pollution and Its Risk on Human Brain Activity in Different Audio Frequency Using Electroencephalogram Complexity.

Iran J Public Health 2016 Oct;45(10):1332-1339

Dept. of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran; Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, Iran.

Background: Noise pollution is one of the most harmful ambiance disturbances. It may cause many deficits in ability and activity of persons in the urban and industrial areas. It also may cause many kinds of psychopathies. Therefore, it is very important to measure the risk of this pollution in different area.

Methods: This study was conducted in the Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences from June to September of 2015, in which, different frequencies of noise pollution were played for volunteers. 16-channel EEG signal was recorded synchronously, then by using fractal dimension and relative power of Beta sub-band of EEG, the complexity of EEG signals was measured.

Results: As the results, it is observed that the average complexity of brain activity is increased in the middle of audio frequency range and the complexity map of brain activity changes in different frequencies, which can show the effects of frequency changes on human brain activity.

Conclusion: The complexity of EEG is a good measure for ranking the annoyance and non-auditory risk of noise pollution on human brain activity.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5149497PMC
October 2016

Muscle synergy extraction during arm reaching movements at different speeds.

Technol Health Care 2017 ;25(1):123-136

Department of Neurology, Mashhad University of Medical Sciences, Mashhad, Iran.

Objective: Muscle synergy is the activation of a group of muscles that contribute to a particular movement. The goal of the present study is to examine the hypothesis that human reaching movements at different speeds share similar muscle synergies and to investigate the kinesiology basis and innervation of muscles.

Methods: Electromyographic activity from six muscles of the upper limb and shoulder girdle were recorded during three movements at different speeds, i.e. slow, moderate and fast. The effect of window length on the RMS signal of the EMG was analyzed and then EMG envelope signals were decomposed using non-negative matrix factorization. For each of the ten subjects, three synergies were extracted which accounted for at least 99% of the VAF. For each movement, the muscle synergies and muscle activation coefficients of all participants were clustered in to three partitions. Investigation showed a high similarity and dependency of cluster members due to the cosine similarity and mutual information in muscle synergy clustering. For further verification, the EMG envelope signals for all subjects were reconstructed.

Results: The results indicated a lower reconstruction error using the center of the muscle synergy clusters in comparison with the average of the activation coefficients, which confirms the current research's hypothesis.
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http://dx.doi.org/10.3233/THC-161256DOI Listing
October 2017

Modeling the virus-immune system interactions in the peripheral bloodstream of HIV infected individuals using a cellular automata model with considering the effects of antiretroviral therapy.

Technol Health Care 2017 ;25(1):59-88

Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

Background: According to the World Health Organization, by the end of last year, about 37 million people throughout the world were diagnosed with AIDS and millions of people die each year from this disease.

Objective: To develop an appropriate model which depicts the mechanism of the dynamics involved in the interactions between HIV and immune system in peripheral bloodstream of HIV infected individuals by considering the phenomena of virus mutation and taking into account the role of latently infected cells in speared of infection and considering the effects of antiretroviral drugs and occurrence of drug resistance in our model in order to assess the results obtained from applying different therapeutic methods.

Methods: Two-dimensional CA model with Moor neighboring was developed. Various agents which they were referring to peripheral bloodstream particles of HIV infected individuals were defined. Then the biological rules were extracted from both expert knowledge and the authoritative articles. The extracted rules were applied for updating the states of these agents. The effects of using antiretroviral drug treatment were considered by applying drug's effectiveness of both of protease and reverse transcriptase inhibitors as two separate inputs of model.

Results: Time evolution curves of concentrations of defined agents were shown as our results. In case of considering no treatment, our results showed that concentrations of healthy CD4+T cells reached the threshold of AIDS after a bout 250 weeks. By applying monotherapy method, the concentrations of these cells remained on the threshold of AIDS for a long time and applying combined antiretroviral therapy (cART) method leaded to increase the concentration of these cells 20% upper than threshold of AIDS. Also, by applying monotherapy and cART compared with no treatment, the concentrations of infected CD4+T cells 10% and 40% decreased further, respectively and for the level of viral load, leads to a reduction of almost 55% and 90%, respectively. Belated treatment, comparison with early treatment, caused almost 10% reduce (increase) in steady state concentrations of healthy (infected) cells.
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http://dx.doi.org/10.3233/THC-161254DOI Listing
October 2017

Effects of box size, frequency of lifting, and height of lift on maximum acceptable weight of lift and heart rate for male university students in Iran.

Electron Physician 2015 Oct 19;7(6):1365-71. Epub 2015 Oct 19.

Ph.D. of Biomedical Engineering, Assistant Professor, Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Introduction: In spite of the widespread use of automation in industry, manual material handling (MMH) is still performed in many occupational settings. The emphasis on ergonomics in MMH tasks is due to the potential risks of workplace accidents and injuries. This study aimed to assess the effect of box size, frequency of lift, and height of lift on maximum acceptable weight of lift (MAWL) on the heart rates of male university students in Iran.

Methods: This experimental study was conducted in 2015 with 15 male students recruited from Tehran University of Medical Sciences. Each participant performed 18 different lifting tasks that involved three lifting frequencies (1lift/min, 4.3 lifts/min and 6.67 lifts/min), three lifting heights (floor to knuckle, knuckle to shoulder, and shoulder to arm reach), and two box sizes. Each set of experiments was conducted during the 20 min work period using the free-style lifting technique. The working heart rates (WHR) were recorded for the entire duration. In this study, we used SPSS version 18 software and descriptive statistical methods, analysis of variance (ANOVA), and the t-test for data analysis.

Results: The results of the ANOVA showed that there was a significant difference between the mean of MAWL in terms of frequencies of lifts (p = 0.02). Tukey's post hoc test indicated that there was a significant difference between the frequencies of 1 lift/minute and 6.67 lifts/minute (p = 0. 01). There was a significant difference between the mean heart rates in terms of frequencies of lifts (p = 0.006), and Tukey's post hoc test indicated a significant difference between the frequencies of 1 lift/minute and 6.67 lifts/minute (p = 0.004). But, there was no significant difference between the mean of MAWL and the mean heart rate in terms of lifting heights (p > 0.05). The results of the t-test showed that there was a significant difference between the mean of MAWL and the mean heart rate in terms of the sizes of the two boxes (p = 0.000).

Conclusion: Based on the results of this study, it was concluded that MAWL and heart rate are influenced by the variables of lifting frequency and the size of the boxes.
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http://dx.doi.org/10.14661/2015.1365DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4623796PMC
October 2015

Nonlinear feature extraction for objective classification of complex auditory brainstem responses to diotic perceptually critical consonant-vowel syllables.

Auris Nasus Larynx 2016 Feb 22;43(1):37-44. Epub 2015 Aug 22.

Medical Physics and Biomedical Engineering Department, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Objective: To examine if nonlinear feature extraction method yields appropriate results in complex brainstem response classification of three different consonant vowels diotically presented in normal Persian speaking adults.

Methods: Speech-evoked auditory brainstem responses were obtained in 27 normal hearing young adults by using G.tec EEG recording system. 170ms synthetic consonant-vowel stimuli /ba/, /da/, /ga/ were presented binaurally and the recurrence quantification analysis was performed on the responses. The recurrence time of second type was proposed as a suitable feature. ANOVA was also used for testing the significance of extracted feature. Post-comparison statistical method was used for showing which means are significantly different from each other.

Results: Dimension embedding and state space reconstruction were helpful for visualizing nonlinearity in auditory system. The proposed feature was successful in the objective classification of responses in window time 20.1-35.3ms, which belonged to formant transition period of stimuli. Also the p value behavior of recurrence time of second type feature as a discriminant feature was close to the nature of the response that includes transient and sustained parts. On the other hand, the /ba/ and /ga/ classification period was wider than the others.

Conclusion: The extracted feature shown in this paper is helpful for the objective of distinguishing individuals with auditory processing disorders in the structurally similar voices. On the other hand, differing nonlinear feature is meaningful in a special region of response, equal to formant transition period, and this feature is related to the state space changes of brainstem response. It can be assumed that more information is within this region of signal and it is a sign of processing role of brainstem. The state changes of system are dependent on input stimuli, so the existence of top down feedback from cortex to brainstem forces the system to act differently.
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http://dx.doi.org/10.1016/j.anl.2015.06.003DOI Listing
February 2016

Generation of a Four-Class Attenuation Map for MRI-Based Attenuation Correction of PET Data in the Head Area Using a Novel Combination of STE/Dixon-MRI and FCM Clustering.

Mol Imaging Biol 2015 Dec;17(6):884-92

Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran.

Purpose: The aim of this study is to generate a four-class magnetic resonance imaging (MRI)-based attenuation map (μ-map) for attenuation correction of positron emission tomography (PET) data of the head area using a novel combination of short echo time (STE)/Dixon-MRI and a dedicated image segmentation method.

Procedures: MR images of the head area were acquired using STE and two-point Dixon sequences. μ-maps were derived from MRI images based on a fuzzy C-means (FCM) clustering method along with morphologic operations. Quantitative assessment was performed to evaluate generated MRI-based μ-maps compared to X-ray computed tomography (CT)-based μ-maps.

Results: The voxel-by-voxel comparison of MR-based and CT-based segmentation results yielded an average of more than 95 % for accuracy and specificity in the cortical bone, soft tissue, and air region. MRI-based μ-maps show a high correlation with those derived from CT scans (R (2) > 0.95).

Conclusions: Results indicate that STE/Dixon-MRI data in combination with FCM-based segmentation yields precise MR-based μ-maps for PET attenuation correction in hybrid PET/MRI systems.
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http://dx.doi.org/10.1007/s11307-015-0849-1DOI Listing
December 2015

Effects of stimulus presentation mode and subcortical laterality in speech-evoked auditory brainstem responses.

Int J Audiol 2014 Apr 7;53(4):243-9. Epub 2014 Feb 7.

* Department of Audiology, School of Rehabilitation, Iran University of Medical Sciences , Tehran , Iran.

Objective: Speech-evoked auditory brainstem responses (ABR) are sensitive to the manipulation of stimulus parameters, including how the stimulus is presented, i.e. monaurally or binaurally. Therefore, this parametric study was designed to compare the effect of binaural and monaural stimuli presentation on speech-evoked ABR features in the parallel assessment of subcortical asymmetry of speech stimuli acoustic elements.

Design: Electrophysiological responses to the speech syllable /da/ were recorded within three stimulus presentation modes.

Study Sample: Forty-eight normal hearing monolingual Persian speakers were included in the current study as volunteer cases.

Results: Shorter right ear latency was observed for peaks A and E, but the overall response timing was comparable within different stimulus presentation modes. Binaural stimulation generally led to larger response than monaural stimulation and affected the encoding of speech spectral elements. Moreover, no significant interpeak interval difference was observed in the sustained portion of responses. Response to the right and left ear stimulation was highly correlated, and a symmetrical pattern was observed between the two ears.

Conclusions: The timing of speech-evoked responses is not related to the stimulus presentation mode; however, binaural stimulation produces more robust responses. Lateral asymmetry in the representation of speech elements was not considerable at the brainstem level.
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http://dx.doi.org/10.3109/14992027.2013.866281DOI Listing
April 2014

Gender disparity in subcortical encoding of binaurally presented speech stimuli: an auditory evoked potentials study.

Auris Nasus Larynx 2014 Jun 30;41(3):239-43. Epub 2013 Oct 30.

Medical Physics and Biomedical Engineering Department, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Objectives: To investigate the influence of gender on subcortical representation of speech acoustic parameters where simultaneously presented to both ears.

Methods: Two-channel speech-evoked auditory brainstem responses were obtained in 25 female and 23 male normal hearing young adults by using binaural presentation of the 40 ms synthetic consonant-vowel/da/, and the encoding of the fast and slow elements of speech stimuli at subcortical level were compared in the temporal and spectral domains between the sexes using independent sample, two tailed t-test.

Results: Highly detectable responses were established in both groups. Analysis in the time domain revealed earlier and larger Fast-onset-responses in females but there was no gender related difference in sustained segment and offset of the response. Interpeak intervals between Frequency Following Response peaks were also invariant to sex. Based on shorter onset responses in females, composite onset measures were also sex dependent. Analysis in the spectral domain showed more robust and better representation of fundamental frequency as well as the first formant and high frequency components of first formant in females than in males.

Conclusions: Anatomical, biological and biochemical distinctions between females and males could alter the neural encoding of the acoustic cues of speech stimuli at subcortical level. Females have an advantage in binaural processing of the slow and fast elements of speech. This could be a physiological evidence for better identification of speaker and emotional tone of voice, as well as better perceiving the phonetic information of speech in women.
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http://dx.doi.org/10.1016/j.anl.2013.10.010DOI Listing
June 2014

A novel viewpoint on parameter estimation in a chaotic neuron model.

J Neuropsychiatry Clin Neurosci 2013 ;25(1):E19

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http://dx.doi.org/10.1176/appi.neuropsych.12010012DOI Listing
September 2013

Study of chaotic behavior of tremor of some Parkinsonians under deep brain stimulation.

Australas Phys Eng Sci Med 2012 Mar 29;35(1):25-30. Epub 2011 Nov 29.

Faculty of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Sardar Jangal, Tehran, Iran.

Deep Brain Stimulation, functional neurosurgery for Parkinson's disease treatment, has three parameters: frequency, pulse width, and voltage. They should be selected appropriately to achieve an effective treatment. In this research, we studied some nonlinear dynamics of Parkinsonian tremor under Deep Brain Stimulation. We recorded finger tremor signals of 8 patients at different voltages as data. To study tremor behavior variation at different voltages, we extracted some nonlinear dynamic features of the data. These features were: embedding space, correlation dimension, largest Lyapunov exponent, entropy and variance of embedding space along x, and y axes. We found that the largest Lyapunov exponents were positive and correlation dimensions of data were not integer, and also all embedding spaces at different voltages had attractors. These observations show that the tremor signal has chaotic behaviors. Also, embedding space variance along x, and y axes in all cases and entropy in the most of them had minimum values at highest voltages in comparison with other voltages. We plotted bar graphs of embedding space variances along x, and y axes at every patient's recorded voltages. A reduction procedure was seen after a threshold in all graphs. As a result, all the chaotic features change with the voltage variation. In the future, it could be possible to select the optimum stimulation voltages by using chaotic features of tremor.
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http://dx.doi.org/10.1007/s13246-011-0111-3DOI Listing
March 2012

A fuzzy-genetic model for estimating forces from electromyographical activity of antagonistic muscles due to planar lower arm movements: the effect of nonlinear muscle properties.

Biosystems 2012 Jan 17;107(1):56-63. Epub 2011 Sep 17.

Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

The aim of this paper is to create a model for mapping the surface electromyogram (EMG) signals to the force that generated by human arm muscles. Because the parameters of each person's muscle are individual, the model of the muscle must have two characteristics: (1) The model must be adjustable for each subject. (2) The relationship between the input and output of model must be affected by the force-length and the force-velocity behaviors are proven through Hill's experiments. Hill's model is a kinematic mechanistic model with three elements, i.e. one contractile component and two nonlinear spring elements. In this research, fuzzy systems are applied to improve the muscle model. The advantages of using fuzzy system are as follows: they are robust to noise, they prove an adjustable nonlinear mapping, and are able to model the uncertainties of the muscle. Three fuzzy coefficients have been added to the relationships of force-length (active and passive) and force-velocity existing in Hill's model. Then, a genetic algorithm (GA) has been used as a biological search method that can adjust the parameters of the model in order to achieve the optimal possible fit. Finally, the accuracy of the fuzzy genetic implementation Hill-based muscle model (FGIHM) is invested as following: the FGIHM results have 12.4% RMS error (in worse case) in comparison to the experimental data recorded from three healthy male subjects. Moreover, the FGIHM active force-length relationship which is the key characteristics of muscles has been compared to virtual muscle (VM) and Zajac muscle model. The sensitivity of the FGIHM has been evaluated by adding a white noise with zero mean to the input and FGIHM has proved to have lower sensitivity to input noise than the traditional Hill's muscle model.
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http://dx.doi.org/10.1016/j.biosystems.2011.09.004DOI Listing
January 2012

The effects of dual-tasking on postural control in people with unilateral anterior cruciate ligament injury.

Gait Posture 2009 Nov 25;30(4):477-81. Epub 2009 Aug 25.

Department of Physical therapy, School of Rehabilitation Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.

Several studies have investigated postural control in anterior cruciate ligament (ACL) deficient patients; yet the contribution of cognitive processing (attention) in the postural control of these patients is still unclear. A dual-task design was used to determine the effects of a concurrent digit span memory task on standing balance in a group of ACL patients (n=27) compared with a group of matched, healthy participants (n=27). In double limb stance, three levels of postural difficulty were studies on a force platform (rigid surface with eyes open, rigid surface with eyes closed, and foam surface with eyes closed). There were three cognitive conditions (no cognitive task, easy cognitive task and difficult cognitive task). For double limb stance, a mixed model analysis of variance showed that in the presence of a cognitive task, postural control was compromised yet there was no interaction between cognitive task difficulty and group (ACL or control). For single limb stance, the more difficult cognitive tasks were associated with lower standard deviations for velocity in the antero-posterior direction and the phase plane portraits. This cognitive task did not appear to compromise postural control in ACL injured patients to a greater extent than unimpaired people. Future studies should examine ACL patients with more severe disabilities and expose them to more demanding dynamic balance conditions to further explore dual-tasking effects.
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http://dx.doi.org/10.1016/j.gaitpost.2009.07.112DOI Listing
November 2009

Effect of dual-tasking on postural control in subjects with nonspecific low back pain.

Spine (Phila Pa 1976) 2009 Jun;34(13):1415-21

Department of Physical Therapy, University of Social Welfare and Rehabilitation, Tehran, Iran.

Study Design: Three factors mixed-design with 1 between-subject and 2 within-subject factors.

Objective: To compare the main effects and interactions of postural and cognitive difficulty on quiet stance between subjects with and without nonspecific low back pain (LBP).

Summary Of Background Data: The interference between postural control and cognitive tasks depends on factors such as sensorimotor/cognitive integrity. Changes in peripheral sensory and muscular systems as well as cognitive processes have been observed in LBP patients. It was hypothesized that the effect of cognitive task on postural performance might be different in subjects with nonspecific LBP as compared with healthy individuals. To the authors' knowledge this has not been investigated before.

Methods: Postural stability was measured by center of pressure parameters while nonspecific LBP (n = 22) and healthy (n = 22) subjects randomly performed quiet standing task with 3 levels of difficulty (rigid-surface eyes open, rigid-surface eyes-closed, and foam-surface eyes-closed) in isolation or concurrently with an easy or difficult digits backward cognitive task.

Results: Subjects with nonspecific LBP had less postural sway than healthy subjects, while postural sway decreased with increase in the level of cognitive difficulty. Nonspecific LBP and healthy subjects had larger postural sway at more difficult sensory conditions such as rigid-surface eyes-closed and foam-surface eyes-closed. The response to dual-tasking was not significantly different between the 2 groups.

Conclusion: The dual-tasking did not change the postural performance of nonspecific LBP subjects with low level of pain and disability differently compared to healthy subjects.
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http://dx.doi.org/10.1097/BRS.0b013e3181a3a917DOI Listing
June 2009

Test-retest reliability [corrected] of center of pressure measures of postural stability during quiet standing in a group with musculoskeletal disorders consisting of low back pain, anterior cruciate ligament injury and functional ankle instability.

Gait Posture 2009 Apr 23;29(3):460-4. Epub 2009 Jan 23.

Department of Physical Therapy, University of Social Welfare and Rehabilitation, Tehran, Iran.

Reliability is a population-specific property, but to the authors' knowledge there has been no study to determine the test-retest reliability of the postural stability measures such as center of pressure (COP) measures in the population of patients with musculoskeletal disorders (MSDs), while their clinical applications have been presented in literature. So, 33 patients with low back pain (LBP), anterior cruciate ligament (ACL) injury and functional ankle instability (FAI) randomly completed postural measurements with three levels of difficulty (rigid surface-eyes open, rigid surface-eyes closed, and foam surface-eyes closed) in two sessions. COP data were used to calculate standard deviation of amplitude, standard deviation of velocity, phase plane portrait, mean total velocity and area (95% confidence ellipse). Relative reliability of these measures was assessed using intraclass correlation coefficient (ICC) and absolute reliability using standard error of measurement (SEM) and coefficient of variation (CV). Also, minimal metrically detectable change (MMDC) was calculated to quantify intervention effects. Among different COP parameters, mean total velocity in all conditions of postural difficulty showed high to very high reliability, with ICC range of 0.74-0.91, SEM range of 0.09-0.40cm/s, CV range of 5.31-8.29% and MMDC range of 0.19-0.79cm/s. Phase plane portrait in anteroposterior-mediolateral (AP-ML) and ML direction were other best parameters with respect to the level of reliability. Mean total velocity and phase plane portrait parameters are suggested as good candidates to use for quantification and assessment of balance performance and identifying those with MSDs.
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http://dx.doi.org/10.1016/j.gaitpost.2008.11.016DOI Listing
April 2009

Saccadic and smooth pursuit eye movements: computational modeling of a common inhibitory mechanism in brainstem.

Neurosci Lett 2008 Dec 14;448(1):84-9. Epub 2008 Oct 14.

Digital Control Laboratory, Faculty of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Somayyeh, Hafez, Tehran 15875-4413, Iran.

The oculomotor system coordinates different types of eye movements in order to orient the visual axis, including saccade and smooth pursuit,. It was traditionally thought that the premotor pathways for these different eye movements are largely separate. In particular, a group of midline cells in the pons called omnipause neurons were considered to be part of only the saccadic system. Recent experimental findings have shown activity modulation of these brainstem premotor neurons during both kinds of eye movements. In this study, we propose a new computational model of the brainstem circuitry underlying the generation of saccades and smooth pursuit eye movements. Similar models have been developed earlier, but mainly looking at pure saccades. Here, we integrated recent neurophysiological findings on omnipause neuron activity during smooth pursuit. Our computational model can mimic some new experimental findings as the similarity of "eye velocity profile" with "omnipause neuron pattern of activity" in pursuit movement. We showed that pursuit neuron activity is augmented during catch-up saccades; this increment depends on the initial pursuit velocity in catch-up saccade onset. We conclude that saccadic and pursuit components of catch-up saccades are added to each other nonlinearly.
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http://dx.doi.org/10.1016/j.neulet.2008.10.019DOI Listing
December 2008