Full Research Paper
Tissue Engineering
Zahra Saghaei Noosh Abadi; Atefe Aghajani; Mohammad Haghpanahi
Volume 7, Issue 1 , June 2013, Pages 1-11
Abstract
We introduce how we may produce an experimental phantom for modeling the mechanical properties of soft tissue. Gelatin materials are used to construct the phantom. Our phantom comprises of two different types of tissue; tumor and background normal tissue. Weight ratio of the dry gelatin and deionized ...
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We introduce how we may produce an experimental phantom for modeling the mechanical properties of soft tissue. Gelatin materials are used to construct the phantom. Our phantom comprises of two different types of tissue; tumor and background normal tissue. Weight ratio of the dry gelatin and deionized water are obtained for producing the young’s modulus of 21 kPa and 102 kPa for the normal tissue and tumor, respectively. This phantom is used in ultrasound elastography with external excitation less than 5%.
Full Research Paper
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Mohsen Naji; Seyed Mohammad Firouzabadi; Sedighe Kahrizi
Volume 7, Issue 1 , June 2013, Pages 13-20
Abstract
The collected electromyogram (EMG) signals from trunk musculature (e.g., rectus abdominis and external oblique muscle) are often contaminated with the heart muscle electrical activity (ECG). This paper introduces a novel method, the Empirical Mode Decomposition, for elimination of ECG contamination from ...
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The collected electromyogram (EMG) signals from trunk musculature (e.g., rectus abdominis and external oblique muscle) are often contaminated with the heart muscle electrical activity (ECG). This paper introduces a novel method, the Empirical Mode Decomposition, for elimination of ECG contamination from EMG signals. The method is compared to a Butterworth high pass filtering. Results obtained from the analysis of generated and experimental EMG signals show that our method outperforms the high pass filtering for elimination of ECG contamination from trunk EMG signals.
Full Research Paper
Rehabilitation Engineering
Ziba Gandomkar; Fariba Bahrami
Volume 7, Issue 1 , June 2013, Pages 21-37
Abstract
Changes in gait pattern are early symptoms in many disorders such as balance and control problems resulted in fall among elderlies. This paper aims at proposing a new set of features extracted from Gait Frieze Pattern (GFP) in order to classify seniors to fallers and non-fallers. For indicating the effectiveness ...
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Changes in gait pattern are early symptoms in many disorders such as balance and control problems resulted in fall among elderlies. This paper aims at proposing a new set of features extracted from Gait Frieze Pattern (GFP) in order to classify seniors to fallers and non-fallers. For indicating the effectiveness of the presented method, the algorithm is used for recognition of different type of abnormal gaits. The introduced method consists of three main steps: extracting the subject from background, generating GFP and aligning them, and building the proposed image from GFP by thresholding followed by morphological operations. For evaluation of the proposed features, video sequences are collected from 8 elderly fallers, 8 non-fallers, and 8 youth while performing standard Timed Up and Go (TUG) test. In addition to TUG test youths are asked to walk fast and pretend to walk with 6 different types of abnormalities (limping, waddling, anterior- posterior sway, lateral sway, dragging, steppage gait). For finding correct classification rate, each time one data is considered as test and others as train and label of train data with the most similarity with test one on the score of normalized cross correlation is assigned to test data. Comparing to conventional TUG test, correct classification data is improved around 20% for faller detection. In addition, correct classification rate for detecting of different abnormalities in gait is approximately 90%.
Full Research Paper
Rehabilitation Engineering
Rahele Mohammadi; Ali Mahloojifar
Volume 7, Issue 1 , June 2013, Pages 39-55
Abstract
A critical issue in designing a self-paced brain computer interface (BCI) system is onset detection of the mental task from the continuous electroencephalogram (EEG) signal to produce a brain switch. This work shows significant improvement in a movement based self-paced BCI by applying a new sparse learning ...
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A critical issue in designing a self-paced brain computer interface (BCI) system is onset detection of the mental task from the continuous electroencephalogram (EEG) signal to produce a brain switch. This work shows significant improvement in a movement based self-paced BCI by applying a new sparse learning classification algorithm, probabilistic classification vector machines (PCVMs) to classify EEG signal. Constant-Q filters instead of constant bandwidth filters for frequency decomposition are also shown to enhance the discrimination of movement related patterns from EEG patterns associated with idle state. Analysis of the data recorded from seven subjects executing foot movement using the constant-Q filters and PCVMs shows a statistically significant 16% (p<0.03) average improvement in true positive rate (TPR) and a 2% (p<0.03) reduction in false positive rate (FPR) compared with applying constant bandwidth filters and SVM classifier.
Full Research Paper
Biomedical Image Processing / Medical Image Processing
Maryam Afzali; Emadoddin Fatemizadeh; Hamid Soltanian Zadeh
Volume 7, Issue 1 , June 2013, Pages 57-64
Abstract
Diffusion tensor magnetic resonance imaging (DTMRI) is a non-invasive method for investigating the brain white matter structure. It can be used to evaluate fiber bundles in the brain but in the regions with crossing fibers, it fails. To resolve this problem, high angular resolution diffusion imaging ...
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Diffusion tensor magnetic resonance imaging (DTMRI) is a non-invasive method for investigating the brain white matter structure. It can be used to evaluate fiber bundles in the brain but in the regions with crossing fibers, it fails. To resolve this problem, high angular resolution diffusion imaging (HARDI) with a large number of diffusion encoding directions is used and for reconstruction, the Q-ball method is applied. In this method, orientation distribution function (ODF) of fibers can be calculated. Mathematical models play a crucial role in the field of ODF. For instance, in registering Q-ball images for applications like group analysis or atlas construction, one needs to interpolate ODFs. To this end, principal diffusion directions (PDDs) of each ODF are needed. In this paper, PDDs are defined as vectors that connect the corresponding local maxima of ODF values. Then, ODFs are interpolated using PDDs.We find the principal direction of ODF of the dataset to be interpolated and then rotate it to lie in the direction of the reference dataset. Now that ODFs are parallel, we apply linear interpolation to generate interpolated data. The proposed method is evaluated and compared with previous protocols. Experimental results show that the proposed interpolation algorithm preserves the principal direction of fiber tracts without producing any deviations in the tracts. It is shown that changes in the entropy of the interpolated ODFs are almost linear and the bloating effect (blurring of the principal directions) can be removed.
Full Research Paper
Biological Computer Modeling / Biological Computer Simulation
Seyed Hojat Sabzpoushan; Fateme Pourhasan Zadeh; Zohre Agin
Volume 7, Issue 1 , June 2013, Pages 65-73
Abstract
A great number of people are diagnosed with a brain tumor, annually. Glioblastoma multiform (GBM) is the most common and deadliest malignant primary brain tumor. Therefore, the study of the growth of GBM is one of the issues considered by researchers. Many mathematical models to simulate the growth of ...
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A great number of people are diagnosed with a brain tumor, annually. Glioblastoma multiform (GBM) is the most common and deadliest malignant primary brain tumor. Therefore, the study of the growth of GBM is one of the issues considered by researchers. Many mathematical models to simulate the growth of GBM brain tumor have been proposed. These models help scientists to understand the process of tumor growth in order to achieve effective treatment. To simulate the tumor growth, a four dimensional (4D) model using cellular automata (CA) method is presented in this paper. A three dimensional (3D) lattice constituted by Voronoi tessellation is used. Spatial distribution of grid points in 3D has been generated by using Random Sequential Addition (RSA). In the utilized lattice, each cell is a polyhedron with various number of edges and neighboring. Delaunay triangulation is applied to find neighboring cells. Each cell in this lattice can be necrotic, non-proliferative, proliferative, non-tumorous or normal. The simulation is capable to exhibit a tumor growth of 0.1 mm to 25 mm in radius. The proposed model has been compared with experimental data in four temporal stages: spheroid, detectable lesion, diagnosis and death. Studies show that the accuracy of the presented model is generally about 85%.
Full Research Paper
Gait Analysis
Afsaneh Yavari; Mostafa Rostami; Ali Esteki; Ali Tanbakoosaz; Mehdi Yousefi Azar Khanian
Volume 7, Issue 1 , June 2013, Pages 75-84
Abstract
Most of the recent biomechanical researches have been focused on the stability of people with disabilities and a few researches have been done on the athletes with high balance skill.The methods of elite athletes in keeping the balance can state valuable information about balance strategies and effective ...
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Most of the recent biomechanical researches have been focused on the stability of people with disabilities and a few researches have been done on the athletes with high balance skill.The methods of elite athletes in keeping the balance can state valuable information about balance strategies and effective parameters on balance. In this study we calculate local dynamical stability of musculoskeletal systems during a hard balance motion. Eight non elite athletes and six elite athletes in Wushu participatedin this study. Kinematic parameters for quantitative assessment of postural fluctuations were recorded by VICON ® Motion Analysis System. Using Lyapunov stability theory, stability and preparation of athletes were evaluated and the best model in performing the balance motion was shown to the coaches. Results from this study showed that motion pattern and preparation of athletes are effective in the displacements of center of mass and center of pressure and finally the stability of athletes.
Technical note
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Mina Amiri; Edmond Zahedi; Fereydoun Behnia
Volume 7, Issue 1 , June 2013, Pages 85-95
Abstract
It is proved that the endothelial (artery inner lumen cells) function is associated with cardiovascular risk factors. Among all the common non-invasive methods employed in the research setting for assessing endothelial function, flow-mediated dilation is the most widely used one. This technique measures ...
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It is proved that the endothelial (artery inner lumen cells) function is associated with cardiovascular risk factors. Among all the common non-invasive methods employed in the research setting for assessing endothelial function, flow-mediated dilation is the most widely used one. This technique measures endothelial function by inducing reactive hyperemia using temporary arterial occlusion and measuring the resultant relative increase in blood vessel diameter via ultrasound. In this paper, the limitations associated with the ultrasound technique are overcome by using the photoplethysmogram (PPG) signal recorded during FMD. The correctness of this approach is investigated by modeling the AC changes of PPG after FMD by a 2nd order autoregressive model. A sensitivity of 78.6%, specificity of 81.6% and total accuracy of 80% were achieved in classification of 16 healthy and 14 diabetic subjects.
