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Detekce začátku a konce komplexu QRS s využitím hlubokého učení
Müller, Jakub ; Šaclová, Lucie (referee) ; Smíšek, Radovan (advisor)
ECG measurement isan essential diagnostic tool for cardiac health, and automation of its analysis can aid to our healthcare to relieve staff workload or improve the quality of automated diagnostics from wearable devices. This work focuses specifically on the QRS complex in the ECG signal, with the main goal of using deep learning methods to detect its onset and offset. In the theoretical introduction, the reader is introduced to the origin of the QRS complex and ECG measurements, artificial neural networks and deep learning. Modified architecture U-Net for 1D signals was chosen to implement the actual method. Data were extracted from five publicly available databases and preprocessed in Matlab. This was followed by moving to the Python environment where parts of the model were implemented using the TensorFlow and Keras libraries, subsequent training, testing of the model and evaluation of the results.
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Detection of pathologies in ECG signals
Němec, Radek ; Mézl, Martin (referee) ; Kašpar, Jakub (advisor)
This thesis attempts with methods for detection of pathologies in ECG signals. The first part is focused on the basic theory of heart anatomy, electrocardiography and individual heart pathologies. The second part describes the preprocessing of ECG signals, detection of QRS complexes and detection of individual pathologies. In the third part the detector is being tested on CSE database and my own measured data.
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Detection of pathologies in ECG signals
Němec, Radek ; Mézl, Martin (referee) ; Kašpar, Jakub (advisor)
This thesis attempts with methods for detection of pathologies in ECG signals. The first part is focused on the basic theory of heart anatomy, electrocardiography and individual heart pathologies. The second part describes the preprocessing of ECG signals, detection of QRS complexes and detection of individual pathologies. In the third part the detector is being tested on CSE database and my own measured data.
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Use of neural networks in classification of heart diseases
Skřížala, Martin ; Tannenberg, Milan (referee) ; Hrubeš, Jan (advisor)
This thesis discusses the design and the utilization of the artificial neural networks as ECG classifiers and the detectors of heart diseases in ECG signal especially myocardial ischaemia. The changes of ST-T complexes are the important indicator of ischaemia in ECG signal. Different types of ischaemia are expressed particularly by depression or elevation of ST segments and changes of T wave. The first part of this thesis is orientated towards the theoretical knowledges and describes changes in the ECG signal rising close to different types of ischaemia. The second part deals with to the ECG signal pre-processing for the classification by neural network, filtration, QRS detection, ST-T detection, principal component analysis. In the last part there is described design of detector of myocardial ischaemia based on artificial neural networks with utilisation of two types of neural networks back – propagation and self-organizing map and the results of used algorithms. The appendix contains detailed description of each neural networks, description of the programme for classification of ECG signals by ANN and description of functions of programme. The programme was developed in Matlab R2007b.
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Modern methods of QRS detection
Richter, Zdeněk ; Hrubeš, Jan (referee) ; Vítek, Martin (advisor)
This work deals with ECG signal and its processing methods. Describing ways of ECG measuring and reports in detail its parts. Next chapter compares some QRS detection methods. One of the sections presents usual testing databases and comparison of described methods. The important part of this bachelor’s thesis is about analysis and design method, which perform detection of QRS complex using counting zero crossings. The last section of the text deals with realization of this method in matlab user interface, determine its success and comparison with other methods.
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Software for QRS detectors performance evaluation
Veverka, Vojtěch ; Vítek, Martin (referee) ; Ronzhina, Marina (advisor)
QRS complex is the most prominent part of ECG signal. Due to its properties, it is used in calculation of heart rate and serves as one of the reference points for automatic delineation of ECG. Therefore, the accurate detection of QRS complexes is very important. This work is focused on creating of software for evaluation of different QRS detection approaches. The first part includes the basics of electrocardiography, the most common methods for QRS detection and also various artifacts that can affect the detection, The practical part is focused on the development of some detectors and the software itself. The detectors are then tested with software using the CSE database of real ECG recordings.
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The principles of software QRS detection
Mosyurchak, Andriy ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
The aim of this project is to introduce the methods of software detection in ECG signals. This thesis includes description of electrocardiogram signal and the main components of the ECG. The following describes the basic methods of QRS complexes detection. In this thesis are realized three methods of QRS detection: Pan-Tompkins algorithm, method based on counting zero crossings and technique using adaptive quantized threshold. Methods are realized by program MATLAB and then tested on CSE database.
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Multilead decision rules in detection of QRS complexes
Šikner, Tomáš ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
QRS complex is the most significant component of the ECG signal. Detection of the QRS complex is the first step to analyze the ECG signal. It serves as a starting point to measure out of the signal. The single-lead detector and the multi-lead detector are carried out in this work. Both detectors are designed in Matlab. The detectors use the characteristic steep slope of the QRS complex to its detection. The detectors were tested on the CSE database.
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Multilead decision rules in delineation of ECG signals
Richter, Zdeněk ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
This work deals with ECG signal measuring and methods of its processing. It compares some of the QRS detection methods and describes some of the testing databases. In this work a detector of QRS complex is realized, it is based on the approach of zero crossings. Next section makes combination of results from separate leads to one, which improves efficiency of detection. One section of this work deals with design and realization delination of ECG signal. In the last part outputs of this delineation are compared with the results of the other authors.
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Detection of pathologies in ECG signals
Němec, Radek ; Mézl, Martin (referee) ; Kašpar, Jakub (advisor)
This thesis attempts with methods for detection of pathologies in ECG signals. The first part is focused on the basic theory of heart anatomy, electrocardiography and individual heart pathologies. The second part describes the preprocessing of ECG signals, detection of QRS complexes and detection of individual pathologies. In the third part the detector is being tested on CSE database and my own measured data.
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