Designing a Synthetic ECG Signal in MATLAB

Import 05/08/2014Hlavním cílem této práce je vytvoření syntetického EKG signálu v prostředí MATLAB na základě analýzy Fourierových řad. Jednotlivé elementy EKG jsou aproximovány matematickým modelem, který je popsán a vysvětlen v teoretické části této práce. Vzniká tak model EKG signálu a to jak fyziologického, tak také některých jeho vybraných patologií. Na specifickém příkladu je tak ukázán návod na aproximaci a vytvoření syntetického modelu jakéhokoli periodického signálu. U vytvořeného syntetického EKG signálu je navíc uživateli dána možnost nastavení amplitudy a délky některých jeho vybraných parametrů. Touto metodikou jsme schopni vytvořit syntetický model EKG signálu s parametry zvolenými podle potřeby, který můžeme využít například jako základ pro kontrolu funkčnosti detektoru délky jednotlivých vln či intervalů apod. Druhá část této práce je věnovaná dalším tématům spojeným s EKG, jako je simulace rušení a následná filtrace EKG nebo transformace signálu do frekvenční oblasti. Vše je provedeno u reálných EKG signálů načtených uživatelem.The main point of this thesis is to design a synthetic signal using MATLAB based on the theory of Fourier series. Each ECG element is approximated by the mathematical model which is described in the theoretical part of the thesis. This way the synthetic model is made – either physiological or pathological. A practical example shows an instruction of any periodical signal approximation. There is also an option for the user to set the size of amplitude or the length of some ECG parameters. By this method it is possible to create a synthetic model of ECG signal with specific parameters chosen for the user’s needs, which can be used for example to control the function of the ECG length and amplitude size detector. The second part focuses on the different topics related with ECG as the simulation of the noise and filtering ECG or the transformation of the signal to the frequency domain. Both applied to the real ECG signals chosen by the user.450 - Katedra kybernetiky a biomedicínského inženýrstvívýborn

Novel characterization method of impedance cardiography signals using time-frequency distributions

The purpose of this document is to describe a methodology to select the most adequate time-frequency distribution (TFD) kernel for the characterization of impedance cardiography signals (ICG). The predominant ICG beat was extracted from a patient and was synthetized using time-frequency variant Fourier approximations. These synthetized signals were used to optimize several TFD kernels according to a performance maximization. The optimized kernels were tested for noise resistance on a clinical database. The resulting optimized TFD kernels are presented with their performance calculated using newly proposed methods. The procedure explained in this work showcases a new method to select an appropriate kernel for ICG signals and compares the performance of different time-frequency kernels found in the literature for the case of ICG signals. We conclude that, for ICG signals, the performance (P) of the spectrogram with either Hanning or Hamming windows (P¿=¿0.780) and the extended modified beta distribution (P¿=¿0.765) provided similar results, higher than the rest of analyzed kernels.Peer ReviewedPostprint (published version

Synchrosqueezed Wave Packet Transforms and Diffeomorphism Based Spectral Analysis for 1D General Mode Decompositions

This paper develops new theory and algorithms for 1D general mode decompositions. First, we introduce the 1D synchrosqueezed wave packet transform and prove that it is able to estimate the instantaneous information of well-separated modes from their superposition accurately. The synchrosqueezed wave packet transform has a better resolution than the synchrosqueezed wavelet transform in the time-frequency domain for separating high frequency modes. Second, we present a new approach based on diffeomorphisms for the spectral analysis of general shape functions. These two methods lead to a framework for general mode decompositions under a weak well-separation condition and a well different condition. Numerical examples of synthetic and real data are provided to demonstrate the fruitful applications of these methods.Comment: 39 page

Extracting a shape function for a signal with intra-wave frequency modulation

In this paper, we consider signals with intra-wave frequency modulation. To handle this kind of signals effectively, we generalize our data-driven time-frequency analysis by using a shape function to describe the intra-wave frequency modulation. The idea of using a shape function in time-frequency analysis was first proposed by Wu. A shape function could be any periodic function. Based on this model, we propose to solve an optimization problem to extract the shape function. By exploring the fact that s is a periodic function, we can identify certain low rank structure of the signal. This structure enables us to extract the shape function from the signal. To test the robustness of our method, we apply our method on several synthetic and real signals. The results are very encouraging