Sharif Digital Repository

Human posture control is a complex issue in biomechanics. Human body is unstable without any controller. The stabilization of the body is achieved by the activation of the muscles and creating the joint torques. In this paper, human body in upright standing position has been modeled using an inverted double pendulum. Since the body parameters are different among the individuals, it is assumed that these parameters are not known exactly and are uncertain. An adaptive controller based on the inverse dynamics in addition to parameter adaptation law has been designed. The simulation of the system using this controller shows the effectiveness of the proposed method in controlling the human... 

This paper presents a biomechanical model with seven degrees of freedom as a seated human exposed to vertical vibration. Experimental data is used to find the stiffness and damping parameters of the model. The data includes values of seat to head transmissibility, driving point mechanical impedance and apparent mass. The multi-objective function is used to obtain theoretical results similar to three different experimental cases. The unknown coefficients are calculated by a genetic algorithm. Improved results, in comparison with previous models, are achieved from the presented model. Next, this modified model is assembled on a quarter car and parameters of the cushion and the suspension... 

An efficient method to automatically recognize basic human actions is proposed to improve the communication between a human and a computer. Human actions are considered as patterns generated by complex non-linear dynamical models. A non-linear dynamical model is used to represent human actions. Gaussian process dynamical models are used to capture the spatial and temporal behaviors of actions. To make the process more efficient a 7-dimensional feature is extracted for each action. Although the extracted feature vector is compact compared to a high-dimensional temporal pattern, it can efficiently discriminate among different actions. The tests run on CMU MoCap database with SVM show promising... 

Advanced control techniques are required for the vibrations suppression of the seated human body in different places like automotive and public transportation lines. In this paper, an active multivariable control strategy is applied to a seated human body model and results are simulated and examined via MATLAB. Dynamic equations of the model are derived using Lagrange method and they are linearized around the equilibrium point of the system. After assessing the deficiencies of the previous models and control strategies proposed for the human body, an active control method is presented based on pole placement analysis. This control strategy is designed for a realistic model of the human body... 

Lipoproteins are biochemical compounds containing both proteins and lipids. These particles carry chemicals like cholesterol and triglycerides that are not soluble in aqueous solutions. This paper presents modeling of lipoprotein system using coarse grain molecular dynamics technique and stability analysis of this system in a water solution like blood. A high density lipoprotein (HDL) that consists of two annular monomers is modeled. Also there are lipid bilayers located in center of the rings, so the whole HDL and lipid bilayers are called lipoprotein system. First, all atom model is provided and then coarse-grain model is obtained using MARTINI technique. Modeling of the system in all atom... 

Modeling is one of assessing tools for better understanding of human body organs and study of diseases. One of the brain diseases is ADHD, which has been studied before, mostly by means of EEG signals. In this paper, the mean-field model, which is a model of neuron-population spiking, and the Power Spectrum of the resulting spikes have been studied by changing parameters of model. The results show that there is a meaningful relationship between firing activity of ADHD patients neuron population and the parameters of mean-field model and Power Spectrum of spikes. In addition, the effects of stimulant medications for ADHD patients on firing activity and power spectrum of firing activity of... 

Radiofrequency coils provide high-resolution magnetic resonance (MR) imaging of human tissues. A small RF coil produces MR images with a higher resolution compared to the commercial volume MR coils from mass limited samples. Signal to noise ratio (SNR) plays a key role in the optimal design of receiver radiofrequency coils. In this work, we present a three-loop saddle coil suitable for MR imaging of digits of the human body. The geometry of the introduced coil is optimized to achieve the highest SNR. The coil performance is evaluated through comparing the measured SNR maps of the optimal coil derived from MR images of a saline phantom with the corresponding measured SNR maps of a commercial... 

Hand pose estimation is one of the most attractive research areas for image processing. Among the human body parts, hands are particularly important for human–machine interactions. The advent of commercial depth cameras along with the rapid growth of deep learning has made great progress in all image processing fields, especially in hand pose estimation. In this study, using depth data, we introduce two hybrid deep neural networks to estimate 3D hand poses with fewer computations and higher accuracy compared with their counterparts. Due to the fact that the dimensions of data are reduced while passing through successive layers of networks, which causes data to be lost, we use the concept of... 

In this paper, we propose a frequency-independent method for calculation of scattered electromagnetic (EM) fields by the human body in millimeter-wave (MMW) band. The surface of the body is accurately modeled by non-uniform rational B-spline (NURBS) surfaces and is illuminated by a plane wave. The scattered EM fields are formulated by physical optics (PO) approximation. This approximation yields PO surface highly oscillatory integrals that are solved by numerical steepest descent path (NSDP) method, frequency-independently. This paper provides an efficient and accurate method for considering human body in indoor propagation, surveillance and medical imaging, and detection of human body by... 

Computed Tomography (CT) medical images show a specific part of human body and present it in a digital form. Lossless image compression is one of the medical imaging applications. To implement such application on hardware we need a simple and fast algorithm. Differential pulse code modulation (DPCM) is a simple and efficient method for transforming image. In this paper best predictor for DPCM introduce in a manner in which has the best result in compression and also be efficient for hardware implementation. After transforming image by DPCM, Huffman encoding used to compress image. We introduce this method with application to brain CT images  

Due to various applications of human motion capture techniques, developing low-cost methods that would be applicable in nonlaboratory environments is under consideration. MEMS inertial sensors and Kinect are two low-cost devices that can be utilized in home-based motion capture systems, e.g., home-based rehabilitation. In this work, an unscented Kalman filter approach was developed based on the complementary properties of Kinect and the inertial sensors to fuse the orientation data of these two devices for human arm motion tracking during both stationary shoulder joint position and human body movement. A new measurement model of the fusion algorithm was obtained that can compensate for the... 

Human motion tracking has many applications in biomedical and industrial services. Low-cost inertial/magnetic sensors are widely used in human motion capture systems to obtain the orientation of the human body segments. In this paper, we have presented a quaternion-based unscented Kalman filter algorithm to fuse inertial/magnetic sensors measurements for tracking human arm movements. In order to have a better estimation of the orientation of the forearm and the upper arm, a constraint equation was developed based on the relative velocity of the elbow joint with respect to the inertial sensors attached to the forearm and the upper arm. Also to compensate for fast body motions, we adapted the...