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Heart beat representation for classification
Smíšek, Radovan ; Janoušek, Oto (referee) ; Ronzhina, Marina (advisor)
Selection of ECG segment plays a significant role in design of a heart beat classifier. The type of selected segments influences the classification not only in regard to the type and maximum number of recognized pathological groups but also in regard to the complexity of classification model, which consequently creates indirect demands on the memory of the computer technology used as well as on the time needed for the classification. The thesis is focused on the comparison of success rates of the ECG heart beat classifications in different input segments. The input segments used were QRST, RST, ST-T, QRS, and T. The ECG signal was obtained from isolated rabbit hearts and divided into individual types according to the T-wave amplitude and changes in the ST segment. The signal subsequently enters the artificial neural network where it is classified into predefined types. The network used had twenty-four neurons in the first layer and one neuron in the second layer. Efficiency of the classification is in the conclusion of this thesis.
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Classification of heart beats using artificial neuronal networks
Doležalová, Radka ; Vítek, Martin (referee) ; Ronzhina, Marina (advisor)
This work deals with using of artificial neural networks (ANN) for ECG classification. The issue of ECG and ANN technique are described theoretically at first, the next section describes use of Matlab to design ANN and graphical user interface. ECG data (namely QRST segments from the orthogonal X- lead from seven phases of the experiment) obtained from experiments in isolated hearts of rabbits are used for learning and testing of the classifier. The result of this work is the software with GUI that allows user to set various parameters and structure of ANN. After learning phase, ANN realized in this work able to classify cardiac cycles according to their morphology into seven groups.
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Use of HRV analysis for automatic detection of ischemia in animal isolated heart
Vykoupil, Pavel ; Vítek, Martin (referee) ; Ronzhina, Marina (advisor)
This paper deals with HRV analysis, creating segments for this analysis, calculating HRV parameters and their classification for automatic detection of ischemia. First part of the work is dedicated to theoretical describtion of heart anatomy, ECG reading, its processing and methods of HRV analysis. Next part of this work outline the principle of creating segments used for calculation of HRV parameters. Last part of the work indtroduces classification of said parameters with the help of multilayered neural networks and finding their best possible setup based on least classification error and computing time achieved. Calculation of HRV parameters and classification was realized using software Matlab.
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ECG classification using methods of HRV analysis
Caha, Martin ; Vítek, Martin (referee) ; Ronzhina, Marina (advisor)
This paper deals with the classification of ECG measured from isolated rabbit hearts during the experiment with repeated ischemia. Classification features were calculated using the methods of heart rate variability analysis. The results were statistically evaluated. Heart rate variability parameters were calculated using Kubios HRV, other calculations were performed in MATLAB. Artificial neural network was created to classify the analyzed parameters to specific groups.
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NQR spectroscopy - design of measurement methods
Procházka, Michal ; Bartušek, Karel (referee) ; Steinbauer, Miloslav (advisor)
Nuclear quadropole spectroscopy is a modern analytical method for detecting specific solid state materials, e.g. explosives, drugs etc. It uses phenomenon of atomic nucleus called nuclear quadrupole moment. NQR method is very similar to common nuclear magnetic resonance (NMR) that is why major principles are explained using NMR. The thesis deals with basic principle of NQR, its usage for explosives detection and also detection of other chemical compounds and many other useful applications. The thesis deals with specific circuit design, techniques for sufficient sensitivity, impedance matching and circuit isolation. Practical part consists of simulations as well as designs of a few impedance transformers, pi-networks, and coils. Also experimental probe was created. In the last part, NQR workplace was assembled and a few chemical compounds were detected. These were KClO3, NaClO3 and NaNO2 . Finally minimum detectable amount of potassium chlorate as the strongest signal of these was determined.
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Wireless system for household appliances voice control
Potůček, Miroslav ; Háze, Jiří (referee) ; Sajdl, Ondřej (advisor)
The thesis deals with using the human voice for controlling electrical appliances by means of wireless technology. It concerns recognition of individual isolated words which form commands. A method based on the distance from the model is used for recognizing the words. The wireless communication is carried out by modules RFM 01/02 whose properties fully conform to the assignment. The practical realization of the network which is capable of switching on and off is described in this work. The network is designed to match the requirements of the task and to be economical.
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Recognition methods for biosignals
Juračka, Zdeněk ; Vítek, Martin (referee) ; Kolářová, Jana (advisor)
The thesis is focused on the recognition methods study used in one-dimensional signal processing. A lot of recognition methods exist, this thesis briefly describes the principle of some of them, e.g. artificial neural networks, fuzzy systems, expert systems and decision trees. Dynamic time warping (DTW) method has been chosen for signal processing available from UBMI database. DTW can be used as a non-linear signal processing method. The result of this method is to determine the similarity of two compared signals on the basis of their distance calculation. One of the reasons for choosing this method was the possibility of various length signal processing. The principle of the method as well as the calculation of the distance between two input data sequences is described in the thesis. DTW path finding method is also mentioned. The method was applied on randomly selected numbers and a set of simulated signals. The method was applied to ECG and action potential signals recorded on the isolated rabbit heart. DTW was used to evaluate shape changes of these signals in repeated phases of the experiment known as ischemia and reperfusion. Selected cardiac cycles were detected and included into different experiment phases on the basis of calculated distance results using DTW. Sensitivity was selected as an evaluative criterion of this classification method. It reached a value of 65%. DTW algorithm was further tested on the selected cardiac cycle mapping to the corresponding minute record in the selected experiment phase. It reached a sensitivity of 68.3%. The motion artifact appearance was monitored using DTW on AP signals. The method functioned more precisely on signals measured in ischemia phases. Along with the above mentioned, the thesis discusses all aspects of heart electrical manifestation activities called as ECG signals and action potentials, such as origin, propagation, recording, post-processing and measuring out.
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Use of higher-order cumulants for heart beat classification
Dvořáček, Jiří ; Kolářová, Jana (referee) ; Ronzhina, Marina (advisor)
This master‘s thesis deals with the use of higher order cumulants for classification of cardiac cycles. Second-, third-, and fourth-order cumulants were calculated from ECG recorded in isolated rabbit hearts during experiments with repeated ischemia. Cumulants properties useful for the subsequent classification were verified on ECG segments from control and ischemic group. The results were statistically analyzed. Cumulants are then used as feature vectors for classification of ECG segments by means of artificial neural network.
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230 V inverter for isolated mains supplied from solar cells
Michálek, Pavel ; Procházka, Petr (referee) ; Martiš, Jan (advisor)
In this thesis is presented detail design of power part of DC/DC converter and output inverter. This device will serve for creating an artificial network in a family house where it will be used for supplying selected household appliances which are designed for use in AC network. The converter will be supplied with DC voltage. This tension will be obtained from a system of photovoltaic panels. The output voltage will have alternate character and it will be close to the network voltage 230 V/50 Hz. In the introductory part of thesis are discussed possible topologies of converters and output inverters. Subsequently are designed individual parts of supply inverter. In the final part there are shown waveforms of important values and is given a thesis evaluation.
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