|
|
Software for ECG analysis
Plch, Vít ; Hejč, Jakub (referee) ; Ronzhina, Marina (advisor)
This bachelor thesis deals with design and construction of tool for analysing electrocardiograms. The theoretical part deals with the origin of the action potential, propagation of the action potential through conduction system of the heart, failure of electrical impulse propagation through the con-duction system; different aspects of disorders, which can be found in experimental electrograms recorded from animal isolated hearts (database of electrograms, the Department of Biomedical En-gineering, FEEC, BUT), are also discussed. Software for electrograms draw and annotation available on the DBME, namely EG_Anotation and EG_RR_View, are described. As a result, the design and construct of ECG_ANN, the tool for the electrograms annotation, is proposed with regard to the advantages and disadvantages of mentioned software. At the end of the bachelor thesis there are the guide for ECG_ANN and discussion about problems which appears in design and construct of this tool.
|
|
|
ECG signal classification
Smělý, Tomáš ; Harabiš, Vratislav (referee) ; Hrubeš, Jan (advisor)
This thesis deals with classification of different types of time courses of ECG signals. Main objective was to recognize the normal cycles and several forms of arrhythmia and to classify the exact types of them. Classification has been done with usage of algorithms of Neural Networks in Matlab program, with its add-on (Neural Network Toolbox). The result of this thesis is application, which makes possible to load an ECG signal, pre-process it and classify its each cycle into five classes. Percentage results of this classification are in the conclusion of this thesis.
|
|
|
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.
|
|
|
ECG signal classification based on SVM
Smíšek, Radovan
Cardiovascular diseases nowadays represent the most common cause of death in Western countries. Long-term ECG recording is modern method, because it allows to detect sporadically occurring pathology. We designed an automatic classifier to detect five pathologies (AAMI standard) by SVM method. The classifier was tested on the entire MIT-BIH Arrhythmia Database with an accuracy of 99.17 %. We also compared the quality of parameters entering the classifier.
|
|
|
Software for ECG analysis
Plch, Vít ; Hejč, Jakub (referee) ; Ronzhina, Marina (advisor)
This bachelor thesis deals with design and construction of tool for analysing electrocardiograms. The theoretical part deals with the origin of the action potential, propagation of the action potential through conduction system of the heart, failure of electrical impulse propagation through the con-duction system; different aspects of disorders, which can be found in experimental electrograms recorded from animal isolated hearts (database of electrograms, the Department of Biomedical En-gineering, FEEC, BUT), are also discussed. Software for electrograms draw and annotation available on the DBME, namely EG_Anotation and EG_RR_View, are described. As a result, the design and construct of ECG_ANN, the tool for the electrograms annotation, is proposed with regard to the advantages and disadvantages of mentioned software. At the end of the bachelor thesis there are the guide for ECG_ANN and discussion about problems which appears in design and construct of this tool.
|
|
|
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.
|
|
|
ECG signal classification
Smělý, Tomáš ; Harabiš, Vratislav (referee) ; Hrubeš, Jan (advisor)
This thesis deals with classification of different types of time courses of ECG signals. Main objective was to recognize the normal cycles and several forms of arrhythmia and to classify the exact types of them. Classification has been done with usage of algorithms of Neural Networks in Matlab program, with its add-on (Neural Network Toolbox). The result of this thesis is application, which makes possible to load an ECG signal, pre-process it and classify its each cycle into five classes. Percentage results of this classification are in the conclusion of this thesis.
|
guest ::
