Sharif Digital Repository

Analysis of performance of fetal heart is very important for monitoring its health. In recent years a lot of research is performed on recording electronic signals from mother abdomen which consist of combination of maternal ECG and fetal ECG. Purpose of this thesis is investigating methods. For evaluation of different methods simulated ECG dataset and Dalsy dataset as real data were used. In this thesis Wavelet and EMD denoising as single channel methods and ICA, PiCA and deflation as multichannel methods are used. At last novel combinations of these methods is proposed which outperforms existing methods  

Noise contamination is inevitable in biomedical recordings. In some cases biomedical recordings are highly contaminated with artifacts which make the effective recovering process hard to achieve. Many different methods have been proposed for artifact removal from biomedical signals but introducing an effective method which can present valuable data for medical analysis, is still an ongoing process.
This dissertation focuses on inter-ictal EEG denoising approaches including ICA-based and EMD-based methods and different combination of these methods. These methods are tested on simulated epileptic recordings which are contaminated with real muscle artifact and EEG signal. The denoised... 

About 42 percent of annual mortality in all around the world is originated from cardiovascular arrhythmias and diseases. One of these arrhythmias is atrial fibrillation whose onset and persistence can produce clot and consequently cause stroke. The basis of our research are upon this idea that dangerous heart arrhythmias do not happen abruptly and there always are some background signs before occurrence of them. In our approach to predict the onset of atrial fibrillation, by analyzing ECG signal in order to extract distinguishing features, we want to classify signals which will terminate Paroxysmal Atrial Fibrillation (PAF) from signals which won’t end with PAF. In this thesis, we propose... 

Adaptive vibration control of a structure under different condition of exciting forces or structural response is the main scope of this research.Using a combination of the pole placement and online Empirical Mode Decomposition (EMD) methods, a new algorithm is proposed for adaptive active control of structural vibration. For this purpose, by structural response which is evaluated from Hilbert-Huang Transform (HHT) and using prior knowledge for corresponding conditions, proper and optimum control forces are applied to structure. Hence, error sources of EMD method in the HHT such as end effects error, mode mixing problem and decomposition resolution are being studied. A modified method based... 

Condition monitoring and fault detection is an important way to provide economy in both time and costs. Many methods are developed for this purpose. Vibration analysis is one of the most important ways in this field. In this thesis, fault detection of mechanical rotary systems with nonlinear and non-stationary nature has been developed by use of empirical mode decomposition (EMD) and Hilbert transform. Firstly the measured signal is transformed into some intrinsic mode functions (IMF’s) by EMD, and then the Hilbert transform is implemented on each IMF. With Hilbert transform, the instantaneous frequency of system and then the mean frequency are obtained. Mean frequency is a key definition...