Musculoskeletal Systems Modeling
Hossein Rostami Barooji; Abdolreza Ohadi; Farzad Towhidkhah
Volume 17, Issue 2 , September 2023, , Pages 120-130
Abstract
Despite the extensive progress in the field of biomechanics of human gait, a suitable gait model with the ability to simulate the control system of the human brain has not yet been presented, especially in 3D mode. The importance of the issue increases when the simulation of human walking is one of the ...
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Despite the extensive progress in the field of biomechanics of human gait, a suitable gait model with the ability to simulate the control system of the human brain has not yet been presented, especially in 3D mode. The importance of the issue increases when the simulation of human walking is one of the main requirements of designers of biomechanical equipment such as artificial organs, wearable robots and humanoid robots. Regarding the constraints and complexities of previous studies, in this research, a forward dynamic 3D model of gait based on sliding mode controller (SMC) is presented, which simulates the walking behavior of healthy individual on the ground in different movement phases. One of the strengths of this research is the comprehensive and analytical review of 3D rotation consequences of the joints coordinate systems, which is done with 11 DOF inverse dynamic model. Based on the obtained results, the SMC controller is well able to produce stable 3D human gait. Also, in 3D gait analysis, the Cardan rotation sequence is not suitable and YXZ order should be used. This outcome is a very useful result for 3D motion generation for human like walking pattern. The results of this study can be used in the design of humanoid robots, active and passive prostheses. Also, the presented model can simulate the walking of an amputee with a prosthesis and the role of the controller in the path, which is very important and beneficial in terms of rehabilitation.
Computational Neuroscience
Maryam Moghadam,; Farzad Towhidkhah; Golnaz Baghdadi
Volume 15, Issue 2 , August 2021, , Pages 111-125
Abstract
In cognition physiology and neuroscience, spatial memory is responsible for the maintenance and recall of information related to environmental details, orientation, and spatial navigation. The brain’s cognitive functions including navigation are executed through correlated and sequential activities ...
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In cognition physiology and neuroscience, spatial memory is responsible for the maintenance and recall of information related to environmental details, orientation, and spatial navigation. The brain’s cognitive functions including navigation are executed through correlated and sequential activities of different regions. According to previous research, navigation is largely related to the activities of the Hippocampus (HPC) and the Medial Temporal Lobe (MTL), and retrieval of spatial memories from these regions is controlled by the frontal region and specifically medial prefrontal cortex (mPFC). In this paper we attempt to provide a navigation cognitive model based on computational concepts focusing on bidirectional interaction between HPC and mPFC. This model is provided considering 1. The lack of a comprehensive cognitive model of navigation on a previously learned path and ambiguities regarding the information transferring between the regions, and 2. Disagreement between available models and the currently known actual information flow occurring within the brain. The model is inclusive of the active brain regions engaged in navigation using the cognitive map. Furthermore, we propose a computational model based on van-der-pol neuron pools and controlling rule-base, which is naturally related to the actual brain activity through the synchrony mechanism for information transfer and the mPFC rule-based control of the medial temporal lobe. Finally, by analyzing and presenting evidence, we have shown that the model can be beneficial and practical for describing cognitive and functional disorders in navigation, also for design and prediction of the outcomes of therapeutic and rehabilitation protocols in diseases related to spatial navigation, such as the Alzheimer’s disease.
Computational Neuroscience
Maryam Sadeghi Talarposhti; Mohammad Ali Ahmadi-Pajouh; Frazad Towhidkhah
Volume 14, Issue 4 , February 2021, , Pages 333-344
Abstract
Human being is capable of performing more than one task simultaneously. This ability has been investigated in many researches. Performing more than one task at the same time has always been a challenging topic in psychology and human perception fields. The output and the effect of two tasks have been ...
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Human being is capable of performing more than one task simultaneously. This ability has been investigated in many researches. Performing more than one task at the same time has always been a challenging topic in psychology and human perception fields. The output and the effect of two tasks have been studied in previous researches for understanding the brain’s performance and also the disease origin and the symptoms. The influence of different difficulty levels has been explored via discrete-continuous motor-cognitive dual-task (DT). To this aim, a manual tracking task combined with discrete auditory stimuli to establish DT procedure. Twenty-five participants in this paradigm were asked to track the target on screen while reacting to the auditory task at the same time. Two levels of difficulty in manual tracking plus a single auditory task (ST) were considered for the experiment. The variability of output via different difficulties was investigated by analyzing factors of error rate and the response time (RT). For this analysis, a Drift Diffusion Model (DDM) method was used. In this 4-parameter model, the drift parameter is assumed to show the difficulty levels. The results show that by applying different drift rates (the average of 0.5, 0.3, and 0.2), the model is consistent with experimental output RT and the drift factor has the potential to be considered as the difficulty factor in the DT procedure.
Neural Engineering / Neuroengineering / Brain Engineering
Ghazaleh Soleimani; Mehrdad Saviz; Farzad Towhidkhah; Hamed Ekhtiari
Volume 14, Issue 3 , October 2020, , Pages 251-266
Abstract
Transcranial direct current stimulation (tDCS) is the most-used non-invasive brain stimulation method. However, the main challenge in tDCS studies is its heterogeneity and large inter-individual variability in response. Brain anatomy, that varies from person to person, can change electric field distribution ...
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Transcranial direct current stimulation (tDCS) is the most-used non-invasive brain stimulation method. However, the main challenge in tDCS studies is its heterogeneity and large inter-individual variability in response. Brain anatomy, that varies from person to person, can change electric field distribution patterns in the brain and should be considered as a source of variation. Previous findings support that tDCS-induced EFs affect brain activity and ultimately change behavioral outcomes. Nonetheless, the exact relationship between EFs and brain activity alterations has not yet been investigated. In this randomized double-blinded sham-controlled crossover study, 14 subjects with methamphetamine use disorders were recruited and tDCS with 2 mA current intensity was applied over the dorsolateral prefrontal cortex. Each subject participated in two sessions for sham or real stimulation with at least a 1-week washout period. In each session, structural and functional MRI during a cue-induced craving task were collected immediately before and after tDCS. Individualized computational head models were simulated based on structural MR images and finite element methods. Group-level analysis of the models showed inter-individual variability across the subjects with maximum electric field intensity in frontal pole (0.3424±0.07). Furthermore, functional data, based on a drug minus neutral contrast, showed that real versus sham stimulation decreased brain activity in superior temporal gyrus and posterior cingulate cortex (P<0.001). However, we did not find a significant correlation between induced EFs and brain activity alterations. In sum, in this study, we suggested a pipeline for integrating electric fields with functional neuroimaging data to bring new insights into the tDCS mechanism of action and future studies are required to establish, or to refute, this conclusion.
Neuro-Muscular Engineering
Reza Hajian; Farzad Towhidkhah
Volume 8, Issue 1 , March 2014, , Pages 19-29
Abstract
Tremor is one of the most frequent movement disorders which is involuntary and approximately sinusoidal. It affects various body joints such as elbow. Tremor on an elbow is considered as extension, flection, and rotation of the forearm. There are miscellaneous types of treatments for tremor one of which ...
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Tremor is one of the most frequent movement disorders which is involuntary and approximately sinusoidal. It affects various body joints such as elbow. Tremor on an elbow is considered as extension, flection, and rotation of the forearm. There are miscellaneous types of treatments for tremor one of which is electrical stimulation. In this research, we study existing stimulation methods in order to reduce tremor and control stimulation pulses. It should be notified that studying these methods requires 1- an electrical stimulator so that one can run natural experiments and estimate the validity of the model, 2- a skeletal- neuromuscular model in order to study the tremor dynamics and the system simulation, and 3- determining an appropriate stimulation scheme and control method in order that one can control the stimulation parameters to reduce tremor. The antagonist muscle stimulation technique for reducing tremor is in the form of either muscle co-contraction or anti-phase stimulation. In the former method, considering the fact that the time-dependent system has time-delay, disturbance, and non-linearities, a robust controller is needed. Hence, in this study, we take advantage of MPC controller because of its features. The results show that MPC controller is more satisfactory than the PID and fuzzy ones used in previous works and also demonstrate that one can theoretically reduce tremor by applying appropriate electrical stimulation.
Neda Kaboodvand; Farzad Towhidkhah; Behzad Iravani; Shahriar Gharibzadeh
Volume 7, Issue 4 , June 2013, , Pages 297-310
Abstract
The central nervous system (CNS) uses a redundant set of joints and muscles to ensure both flexible and stable movements. How the CNS faces the complexity of control problem is not still clear. Modular control is one of the most attractive hypotheses in motor control. In this hypothesis, some motor primitives ...
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The central nervous system (CNS) uses a redundant set of joints and muscles to ensure both flexible and stable movements. How the CNS faces the complexity of control problem is not still clear. Modular control is one of the most attractive hypotheses in motor control. In this hypothesis, some motor primitives (e.g. muscle synergies) are considered as the building blocks that can be combined to present a vast repertoire of movements. EMG signals are required for extracting muscle synergies and NMF (nonnegative matrix factorization) is one of the most accepted methods for extracting synergies. Due to tonic component elimination of EMG signals involved in reaching movements in vertical planes, the standard NMF method is not applicable to extract muscle synergies. In this paper a modified NMF method, so-called semi-NMF, is applied to resolve the tonic component problem. On the other hand, to improve the accuracy of synergies' estimation and to find the global optimum for the optimization problem, we have proposed using HALS method. The proposed algorithm was applied to the experimental EMG recorded in arm reaching movement in the frontal plane. The results showed a good improvement both in accuracy and repeatability of extracted synergies. In addition, extracted muscle synergies were physiologically interpretable.
Speech processing
Shahla Azizi; Farzad Towhidkhah; Farshad Almasganj
Volume 6, Issue 4 , June 2012, , Pages 257-265
Abstract
In present work, recognition of isolated word has been studied. The purpose of this research is to increase the performance of children’s speech recognizer using Vocal Tract Length Normalization. This recognition system has been created to design a speech therapy software. Recognition of correct ...
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In present work, recognition of isolated word has been studied. The purpose of this research is to increase the performance of children’s speech recognizer using Vocal Tract Length Normalization. This recognition system has been created to design a speech therapy software. Recognition of correct and wrong pronunciation and help children to improve it using some feedbacks are the goals of this software. In test phase, some speech data that are related to correct and incorrect pronunciation of 47 words have been utilized. Four Baseline models have been Trained, one for children, one combined model (females and children) and two for Adults (by exploiting one Persian database). Children’s model was trained and tested with data that have been collected from 38 children (5 to 8 years old). These experiments were implemented in HTK toolkit. Poor performance was improved using VTLN. Improvement of adult’s model was more than children’s model.
Biomedical Image Processing / Medical Image Processing
Amin Mohammadian; Hasan Aghaeinia; Farzad Towhidkhah
Volume 6, Issue 3 , June 2012, , Pages 207-218
Abstract
In this paper, a method is proposed based on the prior knowledge from a new subject to improve the performance of person-independent facial expression recognition. First, in order to obtain a basic system, a combination of geometric features and texture descriptor is compared with global features (i.e., ...
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In this paper, a method is proposed based on the prior knowledge from a new subject to improve the performance of person-independent facial expression recognition. First, in order to obtain a basic system, a combination of geometric features and texture descriptor is compared with global features (i.e., mapped face images using the Kernel-PCA and raw data of face images). The results of comparison under noisy conditions were investigated and evaluated by person-dependent/independent cross-validation method. The obtained basic system was evaluated by leave-one-subject-out cross-validation. Since the same subjects are not introduced in both training and test phases, the basic recognition system is person-independent and its performance is substantially lower than that of person-dependent cross-validation case. To improve the performance of the basic system, a method is proposed in which virtual samples are generated based on the prior knowledge from the new subject and are used in learning process. The results show that the recognition rate increases up to 96% for the person-dependent basic system, kernel-PCA method is more sensitive than the others to interpersonal variability, and the recognition rate is significantly (P<0.05) improved up to 91.39% compared to that of person-independent case.
Neuro-Muscular Engineering
Ali Falaki; Farzad Towhidkhah
Volume 5, Issue 2 , June 2011, , Pages 127-141
Abstract
Based on previous studies, human motor control system may apply two control strategies, impedance control and model based control, for learning motor skills and counteracting environmental instabilities. Since interaction among these controllers is not fully studied, the investigation of impedance and ...
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Based on previous studies, human motor control system may apply two control strategies, impedance control and model based control, for learning motor skills and counteracting environmental instabilities. Since interaction among these controllers is not fully studied, the investigation of impedance and model based controllers function during learning period seems desirable. In this study a supervisory controller was used to coordinate the model based and impedance controllers. Coordinating model based controller and impedance controller by using supervisory unit will result in simultaneously adjustment of forward motor command and joint stiffness. In order to evaluate performance of the suggested model, it was applied to arm reaching movements in the presence of external force fields. Results showed that both suitable impedance values and a proper internal model are required to fulfill movements similar to those of humans under different circumstances. Research has shown that central nervous system is able to purposefully modulate arm impedance to counteract environmental disturbances. This study showed that beside this modulation, the maximum motor learning may occur in direction with the least impedance and the most kinematic error. It also concluded that confronting abrupt changes in disturbance, the system managed to decrease error without learning the new dynamic using previous knowledge by supervisory system. A part of this compensation is due to stiffness variations and another part is due to decreasing the influence of model based controller.
Cardiovascular Biomechanics
Vahid Abouie; Farzad Towhidkhah; Vahid Reza Nafisi; Hani Sharifian
Volume 5, Issue 4 , June 2011, , Pages 305-311
Abstract
Today, Dialysis hypotension during hemodialysis process is the most common problems for about 20 to 30 percent of dialysis patients. In order to avoid this hypotension, blood pressure should be measured during dialysis process continuously and noninvasively But it is practically impossible and few devices ...
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Today, Dialysis hypotension during hemodialysis process is the most common problems for about 20 to 30 percent of dialysis patients. In order to avoid this hypotension, blood pressure should be measured during dialysis process continuously and noninvasively But it is practically impossible and few devices for noninvasive and continuous blood pressure measurement are very expensive. Considering this subject, the parameters related to blood pressure should be used to reach this goal. The blood concentrations and heart rate changes are associated with blood pressure in dialysis patients, so in this study, we determined a model by these two parameters in order to predict the blood pressure of hemodialysis patients. After measuring blood concentration, Heart rate and blood pressure from 14 dialysis patients, using neural network model, we determined a new model that can predict blood pressure in dialysis patient by using blood concentration and heart rate data with 3.8 percent error between the real pressure and the pressure that predicted by the model.
Neuro-Muscular Engineering
Mehdi Borjkhani; Farzad Towhidkhah
Volume 4, Issue 2 , June 2010, , Pages 109-122
Abstract
Writing is one of the high practiced and complex movement skills of human. Most of the proposed models for writing are bottom-up models, and therefore they could not reflect the biological aspects of movements in this process. Also there is not any model for illustrating the role of different parts of ...
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Writing is one of the high practiced and complex movement skills of human. Most of the proposed models for writing are bottom-up models, and therefore they could not reflect the biological aspects of movements in this process. Also there is not any model for illustrating the role of different parts of the brain in this task. In this paper we are going to describe some neurological and physiological aspects of the brain operation in the writing task. Then some evidence of prediction in writing and existence of internal models for limbs such as hand are presented. According to these, modeling of writing using model predictive control (MPC) is possible. Based on the presented simulations and experimental results it seems that the modeling of writing by MPC is very similar to the real skill, The proposed model has some advantages such as being consistent with the biological evidence, modeling prediction in writing and high correlation of the statical and dynamical features of the generated letters with those written by human.
Biomimetics
Saeed Rashidi; Seyed Mohammad Reza Hashemi Golpayegani; Ali Fallah; Farzad Towhidkhah
Volume 4, Issue 1 , June 2010, , Pages 33-44
Abstract
In drawing movements, the constraints imposed on the trajectory geometry properties and kinematics are known with two laws: 2/3 power law and isochrony phenomenon. In this paper experiments have been designed to study the relation between two empirical laws in straight and curved patterns of drawing ...
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In drawing movements, the constraints imposed on the trajectory geometry properties and kinematics are known with two laws: 2/3 power law and isochrony phenomenon. In this paper experiments have been designed to study the relation between two empirical laws in straight and curved patterns of drawing movements in 16-18 years old subjects. Providing two models of power is indicated that in drawing movements, invariant features can be defining. These features are independent of subject, direction and size of trajectory and together they can simplify the role of the upper motor control system and decrease the degrees of freedom and the computational complexity.
Saeed Rashidi; Ali Fallah; Farzad Towhidkhah
Volume 4, Issue 2 , June 2010, , Pages 135-148
Abstract
Many methods are introduced for estimating the similarities or differences of time signals. One of theses methods, DTW algorithm, is also a utility for other domains including classification, data mining and matching regions between two time signals. DTW algorithm minimizes points distance between two ...
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Many methods are introduced for estimating the similarities or differences of time signals. One of theses methods, DTW algorithm, is also a utility for other domains including classification, data mining and matching regions between two time signals. DTW algorithm minimizes points distance between two signals by contracting or expanding the time axes to find the corresponding points. In this paper, with modification of the local constraints in DTW, a powerful method is proposed for measuring the global or local similarities between two signals. In addition to increasing the accuracy of signals distance measurements and decreasing the classification error, proposed algorithm is more stable than classic DTW against variations of structure and time signal source. The proposed method for dynamic signature verification was applied to a dataset of signatures from Turkish, Chinese and English people. The results of the experiments based on Fisher, Parzen Window and Support Vectors Machine classifications, showed that equal error rate (EER) is 1.46% and 3.51% with universal threshold for random and skilled forgeries, respectively.
Saeed Rashidi; Ali Fallah; Farzad Towhidkhah
Volume 4, Issue 3 , June 2010, , Pages 219-230
Abstract
Nowadays, fast and accurate algorithms for signature verification are very attractive. In the area of dynamic signature verification, the features are classified into two groups: parametric and functional features. In parametric algorithms, although the speed of features extraction and classification ...
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Nowadays, fast and accurate algorithms for signature verification are very attractive. In the area of dynamic signature verification, the features are classified into two groups: parametric and functional features. In parametric algorithms, although the speed of features extraction and classification process is faster than function based approaches but they are less accurate. The goal of this paper is modeling of the velocity signal that its pattern and properties are stable for a person. With using pole-zero models based on discrete cosine transform, a precise method is proposed for modeling and then features are extracted from strokes. These features are the deference of pole angles of strokes. Applying linear, parzen window and support vector machine classifiers, the proposed algorithm was tested on data set from Persian, Chinese, English and Turkish people and with common threshold, resulted equal error rates of 1.25% and 1.78% in the random and skilled forgeries, respectively.
Speech processing
Ayoub Daliri; Farzad Towhidkhah; Shahriar Gharibzadeh; Yaser Shekofteh
Volume 2, Issue 2 , June 2008, , Pages 123-129
Abstract
Speech production is one of the most complicated physiological systems including different subsystems. These subsystems must work together in a synchronous manner. One of the important sub-systems is the jaw. Although different models have suggested for jaw, no suitable model has been proposed yet to ...
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Speech production is one of the most complicated physiological systems including different subsystems. These subsystems must work together in a synchronous manner. One of the important sub-systems is the jaw. Although different models have suggested for jaw, no suitable model has been proposed yet to consider the interactions between muscles, bones and nervous system. In this paper, using Spring-Damper-Mass and a nonlinear concept, we introduced a novel model for jaw movement during speech production. Experimental data were used to estimate the model parameters. Computer simulation results showed that the model could generate the jaw movement patterns similar to those observed in physiological behavior. Generality and simplicity of the model are two model features useful for more investigation of the jaw movement in different tasks.
Biomechanical Motor Control / Motor Control of Human Movement
Saeed Rashidi; Ali Fallah; Farzad Towhidkhah
Volume 1, Issue 4 , June 2007, , Pages 269-280
Abstract
Dynamic signature verification based on temporal features are more precise than the static methods because in addition to position information of the drawing pattern, it uses local and global features extracted from velocity, acceleration, pressure and pen angle signals, while static methods only use ...
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Dynamic signature verification based on temporal features are more precise than the static methods because in addition to position information of the drawing pattern, it uses local and global features extracted from velocity, acceleration, pressure and pen angle signals, while static methods only use image information. In this study, we segmented the signature patterns using the basic role of velocity in the control process of skilled movements and then the function features were extracted. In order to signal the matching evaluation, we applied five generalized functions and five weighting strategies for score level fusion. The results showed that the correlation criterion had the minimum error. The experiments on the database, consisting of persons of Persian, Chinese and English, showed that the skilled forgeries obtained an equal error rate (EER) of 0.87% and 1.24% for the user and universal thresholds, respectively.
Biological Computer Modeling / Biological Computer Simulation
Azade Ahouraei; Farzad Towhidkhah; Fateme Haji Ebrahim Tehrani; Rasoul Khayati
Volume 1, Issue 1 , June 2007, , Pages 63-69
Abstract
Jaundice (hyperbilirubinemia) is a common disease in newborn babies. Under certain circumstances, elevated bilirubin levels may have detrimental neurological effects. In some cases, phototherapy is needed to lower the level of total serum bilirubin, which indicates the presence and severity of jaundice. ...
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Jaundice (hyperbilirubinemia) is a common disease in newborn babies. Under certain circumstances, elevated bilirubin levels may have detrimental neurological effects. In some cases, phototherapy is needed to lower the level of total serum bilirubin, which indicates the presence and severity of jaundice. Recently, diagnosis and treatment modeling of disease have been considered by many researchers. In this paper, we present two models for classification and prediction of neonatal jaundice. The models are based on recorded data of Iranian Neonates. This study is oriented on the basis of following procedures: a short review on physiology of Jaundice, and then description of the models. Two three-layer feed forward neural networks were used in the modeling. The neural network model for classification is able to specify the type of jaundice, and the model for prediction can evaluate the risk of jaundice for newborns. These models can be used to decrease the risk in the critical cases as well as the cost of treatment.
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.
