Sharif Digital Repository

In this paper, we describe a Gaussian wave-based state space to model the temporal dynamics of electrocardiogram (ECG) signals. It is shown that this model may be effectively used for generating synthetic ECGs as well as separate characteristic waves (CWs) such as the atrial and ventricular complexes. The model uses separate state variables for each CW, i.e. P, QRS and T, and hence is capable of generating individual synthetic CWs as well as realistic ECG signals. The model is therefore useful for generating arrhythmias. Simulations of sinus bradycardia, sinus tachycardia, ventricular flutter, atrial fibrillation and ventricular tachycardia are presented. In addition, discrete versions of... 

A gyroless deterministic attitude determination algorithm based on simulation of sun in eclipse is stated in this paper and has been compared to stochastic filters like extended Kalman filter and unscented Kalman filter. Attitude determination with low cost sensors such as magnometer and sun sensor results in usage of recursive algorithms such as Kalman filter which has the probability of divergence, but with deterministic point to point algorithm such as the one introduced in this paper we can be sure to have an attitude determination with a fixed maximum error. Proposed method has been compared with Extended Kalman Filter and Unscented Kalman filter due to its modeling error, robustness... 

Fault detection has always an important role in maintaining the system stability and assuring satisfactory and safe operation. In this paper a method based on system identification is used for fault detection on a nuclear reactor. The combination of Extended Kalman Filter and recursive Least Square are used to identify the system parameters. Another goal of this paper is design of a fault tolerant control system for a nuclear reactor during power change operation. The proposed controller is an adaptive neuro-fuzzy controller based on emotional learning. Performance of the controller in term of transient response and robustness against failure is very good and outstanding  

This paper presents a novel heat based measurement model for attitude determination (AD) using temperature data via two filtering techniques. Within the space environment, the Sun and Earth are considered as the major sources of external radiation that affect satellite surface temperature. In order to perform the required AD task, the satellite surface temperatures are related to its attitude via a proposed heat model (HM), assuming that the satellite navigational data is available. The proposed HM relates the net heat flux of three satellite orthogonal surfaces to its attitude. Filtering implementation of the proposed HM using the Unscented Kalman Filter (UKF) for AD is the key contribution... 

This paper proposes a new method to improve accuracy and real-time performance of inertial joint angle estimation for upper limb rehabilitation applications by modeling body acceleration and adding low-cost markerless optical position sensors. A method based on a combination of the 3D rigid body kinematic equations and Denavit-Hartenberg (DH) convention is used to model body acceleration. Using this model, body acceleration measurements of the accelerometer are utilized to increase linearization order and compensate for body acceleration perturbations. To correct for the sensor-to-segment misalignment of the inertial sensors, position measurements of a low-cost markerless position sensor are... 

In this study, a novel approach based on a modified Kalman filter algorithm is presented to directly estimate and measure the surface topography of samples by trolling mode atomic force microscopy. Trolling mode atomic force microscopy was introduced as an atomic force microscopy alternative to overcome imaging problems in liquid environments by reducing the liquid-resonator interaction forces. In conventional imaging techniques, the time to reach the steady state periodic motion of the oscillating probe restricts scanning speed. To overcome this limitation, we propose a novel imaging technique for trolling mode atomic force microscopy based on the system dynamics model and using the... 

This paper presents an efficient algorithm based on a nonlinear dynamical model for the precise extraction of the characteristic points of electrocardiogram (ECG), which facilitates the HRV analysis. Determining the precise position of the waveforms of an ECG signal is complicated due to the varying amplitudes of its waveforms, the ambiguous and changing form of the complex and morphological variations with unknown sources of drift. A model-based approach handles these complications; therefore a method based on the usage of this concept in an extended Kalman filter structure has been developed. The fiducial points are detected using both the parameters of Gaussian-functions of the model, and... 

Unlike a single-body approach, modeling based on a two-body approach has been employed to prepare the required system dynamic model as a time update equation in the applied filtering technology and measurement data for the estimation process. This more precise mathematical model enabled better understanding about the dynamics of the change in the aircraft mass properties during the airdropping operation. The problem is defined as estimation of the optimal mass properties parameters for the best possible fit of the model output to the real data. The parameter estimation problem is investigated by a nonlinear filtering methodology in two sequential steps. In the first step, the single extended... 

In this paper, a novel nonlinear joint dynamical model is presented, which is based on a set of coupled ordinary differential equations of motion and a Gaussian mixture model representation of pulsatile cardiovascular (CV) signals. In the proposed framework, the joint interdependences of CV signals are incorporated by assuming a unique angular frequency that controls the limit cycle of the heart rate. Moreover, the time consequence of CV signals is controlled by the same phase parameter that results in the space dimensionality reduction. These joint equations together with linear assignments to observation are further used in the Kalman filter structure for estimation and tracking. Moreover,...