Square Root Implementation of Marginalized Particle Extended Kalman Filter with an Application in ECG Processing
Hamed
Danandeh Hesar
Ph.D Student, Department of Biomedical Engineering, K. N. Toosi University of Technology, Tehran, Iran
author
Maryam
Mohebbi
Assistant Professor, Department of Biomedical Engineering, K. N. Toosi University of Technology, Tehran, Iran
author
text
article
2018
per
Marginalized particle extended Kalman filter (MP-EKF) takes advantage of both extended Kalman filter and particle filter frameworks to estimate nonlinear ECG dynamic models (EDMs) with reduced number of calculations in comparison to typical particle filters. However, due to existence of Kalman filter framework inside MP-EKF, some limitations are introduced in implementation of MP-EKF especially in embedded systems with finite numerical accuracies. In this paper, for the first time, we propose a square root filtering strategy for MP-EKF which alleviates these restrictions using factorization. Typical or other square-root Kalman filters cannot be employed inside MP-EKF due to presence of minus operations in some equations of MP-EKF. However, our method can be implemented in MP-EKF structure. The proposed method can be used in any EDM previously used by EKF based frameworks in the field of ECG processing.
Iranian Journal of Biomedical Engineering
Iranian Society for Biomedical Engineering
5869-2008
11
v.
4
no.
2018
275
289
https://www.ijbme.org/article_31340_e36a5c1b94e075d98aa66f6b34eecad9.pdf
dx.doi.org/10.22041/ijbme.2018.78590.1313
Modeling Two Delay System of Insulin-Glucose based on Noninvasive Continuous Measurement
Reza
Vosoughi
Department of Biophysics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran - Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, Iran
author
Armin
Allahverdy
Department of Radiology, Sari School of Allied Medical Sciences, Mazandaran University of Medical Sciences, Sari, Iran
author
Sajjad
Shafiekhani
Department of Biophysics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran - Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, Iran
author
Amir Homayoun
Jafari
Associate Professor, Department of Biophysics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran - Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, Iran
author
text
article
2018
per
In recent decades, due to the increased prevalence of diabetes and its chronic complications, glucose measurement, modeling of glucose-insulin system and glucose control have been especially important. Since the type I diabetes does not secrete insulin, cells do not absorb glucose, and thus the blood glucose level increase. In order to control your blood sugar, insulin should besubcutaneously injected into the body under complex, controlled conditions. If the level of insulin increases beyond the natural physiological range, there is a risk of death. There are various treatments for diabetes, the main treatment of which is insulin therapy. Monitoring the patient's blood sugar level continuously during the day and night is a very good treatment strategy, since it controls the patient's blood sugar level in a safe area with the lowest amount of insulin injected at the required times. This mechanism avoid the hyperglycemia (blood glucose levels greater than 120 mg/dl) and hypoglycemia (blood sugar less than 65 mg / dl). To achieve this goal, a two delay model has been developed to model blood glucose levels continuously during time. Some of the parameters of this model are estimated using the genetic algorithm to achieve the best fitness between the dynamics of the model with the experimental data obtained in this study. As a result, the developed model of this study can dynamically obtain blood glucose continuously during time, consequently it can predicts the insulin dynamics required to be injected into the patient to control the amount of blood glucose in the normal range. Therefore this controlling system is capable of preventing hypoglycemia and hyperglycemia.
Iranian Journal of Biomedical Engineering
Iranian Society for Biomedical Engineering
5869-2008
11
v.
4
no.
2018
291
301
https://www.ijbme.org/article_31321_29479f07da3ec24592ad99757f5a626e.pdf
dx.doi.org/10.22041/ijbme.2018.80819.1321
Molecular Dynamics Simulation of PASylated G-CSF and Proposing a Modified PAS String Sequence in order to Improve Drug’s Properties
Abbas
Gholami
MSc Graduated, Mechanical Engineering Department, Sharif University of Technology, Tehran, Iran
author
Amir
Shamloo
Associate Professor, Mechanical Engineering Department, Sharif University of Technology, Tehran, Iran
author
text
article
2018
per
PASylation is a new and effective way to increase the half-life of pharmaceutical proteins. This method is an alternative of PEGylaion and uses the natural polymers of Proline, Alanine, and Serine (PAS) amino acids in its structure. In this paper, we have studied the pharmacokinetic properties of PASylated Granulocyte-colony stimulating factor (G-CSF) using Molecular Dynamics (MD) simulation for three different PAS strings length 210, 420 and 630. We studied several important mechanical quantities involving in enhancing half-life time of the conjugated protein like root-mean-square distance (RMSD), hydrodynamic volume, protein total energy and its hydrophilicity and we found out volume expansion, increase in hydrophilicity amount and coil structure in PASylation are main mechanical properties influencing half-life time. We also found out that RMSD will be modified by PASylation while energy level shows erratic behavior examining the mentioned residues properties, we have also offered a modified sequence for PAS string according to the importance of different parameters in PAS string’s function.
Iranian Journal of Biomedical Engineering
Iranian Society for Biomedical Engineering
5869-2008
11
v.
4
no.
2018
303
311
https://www.ijbme.org/article_31339_a2dc8d5a64aed7d2610d0bb314a94fc3.pdf
dx.doi.org/10.22041/ijbme.2018.81637.1324
Automatic Stage Scoring of Single-Channel Sleep EEG using Discrete Wavelet Transform and a Hybrid Model of Simulated Annealing Algorithm and Neural Network
Sobhan
Sheykhivand
M.Sc. Student, Biomedical Engineering Department, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
author
Tohid
Yousefi Rezaii
Assistant Professor, Biomedical Engineering Department, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
author
Zohreh
Mousavi
Ph.D Student, Department of Mechanical Engineering, Faculty of Mechanical Engineering, University of Tabriz, Tabriz, Iran
author
Saeed
Meshgini
Assistant Professor, Biomedical Engineering Department, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
author
text
article
2018
per
Using an intelligent method to automatically detect sleep patterns in medical applications is one of the most important challenges in recent years to reduce the workload of physicians in analyzing sleep data through visual inspection. In this paper, a single-channel EEG-based algorithm is used to automatically identify sleep stages using discrete wavelet transform and a hybrid model of simulated annealing and neural network. The signal is decomposed using a discrete wavelet transform into seven levels and statistical properties of each level is calculated. To optimize and reduce the dimensions of feature vectors, hybrid model of simulated annealing algorithm and multi-layered neural network are used. Then ANOVA test is applied to validate the selected features. Finally the classification is performed on the validated features by a perceptron neural network with a hidden layer, which provides an average of 90% classification ccuracy for 2 to 6-class classification of different steps of sleep EEG. Suggesting that the proposed method has higher degree of success in classifying sleep stages compared to the existing methods.
Iranian Journal of Biomedical Engineering
Iranian Society for Biomedical Engineering
5869-2008
11
v.
4
no.
2018
313
325
https://www.ijbme.org/article_31189_a921bf87583842ed714764940cafabd0.pdf
dx.doi.org/10.22041/ijbme.2018.82011.1327
Estimation of Lumbar Spine Load Sharing using a Detailed Finite Element Model driven by X-Ray Kinematics in Flexion Task
Iraj
Dehghan Hamani
M.Sc. Student, Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran
author
Navid
Arjmand
Associate Professor, Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran
author
text
article
2018
per
Spinal diseases are prevalent and costly. Excessive mechanical loads on the spine play a crucial role in the etiology of back disorders. To estimate spinal loads one needs to calculate unknown muscle forces through either an optimization or EMG-driven approach. Both approaches involve several assumptions and simplifications regarding anatomy of muscles, mechanical properties of the spinal tissues, and estimation of the muscle forces. An alternative approach is to estimate spinal loads through effect of muscle forces, i.e., kinematics generated by muscles rather than forces generated by muscles. The present study hence aims to estimate spinal loads using a detailed finite element (FE) model of the T12-S1 spine driven by kinematics obtained through upright x-ray imaging. For this, kinematics (angular and translational displacements) of the T12 through S1 vertebrae were first measured in vivo in three healthy individuals when performing flexion from relaxed upright posture. The measured kinematics were subsequently prescribed to the FE model to estimate load sharing among the joint structures. In agreement with the measured data, the L1-L2, L2-L3, L3-L4 and L4-L5 average intradiscal pressure was estimated to be ~2.6, ~2.8, ~2.1 and ~2 MPa in flexion, respectively.
Iranian Journal of Biomedical Engineering
Iranian Society for Biomedical Engineering
5869-2008
11
v.
4
no.
2018
327
335
https://www.ijbme.org/article_31195_a1ae9051adcdf2a0027f2bcf61358487.pdf
dx.doi.org/10.22041/ijbme.2018.85502.1341
Feature Extraction for Object Recognition Inspired by Human Visual System
Hiwa
Sufikarimi
Ph.D Student, Electronic School, Electrical Engineering Faculty, Iran University of Science and Technology, Tehran, Iran
author
Karim
Mohammadi
Professor, Electronic School, Electrical Engineering Faculty, Iran University of Science and Technology, Tehran, Iran
author
text
article
2018
per
In this paper, we tried to present a robust and reliable approach to object recognition by inspiring human visual system. A famous model, inspiring mammalian visual system, is HMAX (Hierarchical Model and X). It shows significant accuracy rates on object recognition tasks. However, there are some differences between this model and human visual system. Indeed cortex's functions are not properly modeled. Unrepeatability under fixed conditions, redundancy, high computing load and being slow are some drawbacks of HMAX. By modeling the secondary visual cortex and adding to the HMAX, we tried to introduce a more accurate model of the human visual system and cover the drawbacks of the previous models. The proposed approach functionally mimics the secondary visual cortex. Attending to high-level features, selecting discriminative and repeatable features, it has higher performance than standard HMAX. The added parts have negligible computation load. Therefore, it does not slow down this model. On the contrary, by selecting brief and useful features, the speed of the model is increased. The proposed approach is compared to the standard HMAX in terms of speed and accuracy rate. The results showed the advantage of proposed approach rather than the standard HMAX. In addition, the effect of the number of features and training images on their performance was shown. It is shown that the proposed approach has a better performance than the standard HMAX especially when the number of feature and training images is small.
Iranian Journal of Biomedical Engineering
Iranian Society for Biomedical Engineering
5869-2008
11
v.
4
no.
2018
337
349
https://www.ijbme.org/article_31648_d737afdfc16676a145f8716ed0f29011.pdf
dx.doi.org/10.22041/ijbme.2018.85614.1343
Estimation of Low Back Muscles and Joints Forces in Various Physical Tasks using a Combined Optimization-EMG based Spinal Model
Yousef
Mohammadi
Ph.D Student, Facualty of Biomechanics, Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
author
Rasoul
Abedi
Ph.D Student, Facualty of Biomechanics, Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
author
Navid
Arjmand
Associate Professor, Facualty of Biomechanics, Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran
author
Gholamreza
Ataei
Instructor, Faculty of Paramedical Sciences, Department of Radiological Technology, Babol University of Medical Sciences, Babol, Iran
author
Nasser
Fatouraee
Associate Professor, Facualty of Biomechanics, Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
author
text
article
2018
per
The growth of low back pain and disoreders are increasing in different societies. Furthermore,the direct in vivo measurement of spinal and muscle forces is so difficult. Hence, the use of musculoskeletal biomechanical models has been emerged applicably as a tool for calculating and estimating spinal forces under various activities. Thus, the purpose of this study is to estimate the mentioned forces with different methods especially in lifting tasks. To this end, a six-joint model with eighteen degrees of freedom and 76 trunk muscle fascicles has been developed. Due to more number of unknowns (muscle forces) than equilibrium equations, the system is redundant and the problem is indeterminate to be solved. So the electromyography assisted optimization (EMGAO) approach is used for estimating muscle forces. Since foregoing EMG muscle forces do not satisfy equilibrium equations, correction coefficients have been used for satisfying equilibrium at all lumbar joint levels. According to results in an identical task, all of the approaches indicated substantial differences in correction coefficients for each muscle. Although the stability and muscle forces are different in various EMGAO methods, spinal compression and shear forces are closer to each other in these methods. For validation of results, the intradiscal pressure (IDP) at L4-L5 in various methods are in agreement with in vivo IDP value of an experimental test measurement so that both of them reported this quantity in the range of 0.3-1.8 (MPa).
Iranian Journal of Biomedical Engineering
Iranian Society for Biomedical Engineering
5869-2008
11
v.
4
no.
2018
351
363
https://www.ijbme.org/article_31454_dee03a86db25a243872b6991fd79fde5.pdf
dx.doi.org/10.22041/ijbme.2018.85561.1344