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Detrending heart rate variability signal with empirical mode decomposition EMD
Foltová, Anežka ; Janoušek, Oto (referee) ; Kubičková, Alena (advisor)
HRV analysis is an important indicator of pathophysiological examination. R-R waves are used for detection and analysis of ECG interval. R-R intervals can be analyzed by various methods. During spectral analysis is an often phenomenon disturbing non-stationary trend, which needs to be removed. In this paper, which deals about detrending, is mainly introduced Empirical mode decomposition (EMD) which is popular in recent years. Subsequently, this method is being compared to the method of wavelet transformation and Smoothness prior apprach (SPA).
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Sympatovagal balance analysis
Rusz, Jakub ; Ronzhina, Marina (referee) ; Janoušek, Oto (advisor)
The main focus of this work is to describe and implement a method to analyze sympathovagal balance. The theoretical part begins with electrocardiogram origin and measurement followed by heart rate variability explanation and a method of tachogram creation. The chapter is finished by description of wavelet transform as a means for tachogram processing and obtaining the sympato-vagal balance coeficient. Practical part of work focuses on developing a solution in Matlab for this problem. The R detector, tachogram creation and wavelet transform processing scripts with sympato-vagal balance assesment are fully described along with an example of their outputs. The work is finished with a conclusion of the findings and the assessment of sympato-vagal balance form them, which is unfortunately not so simple.
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Correlation dimension analysis for heart rate variability analysis
Ptáček, Ondřej ; Čmiel, Vratislav (referee) ; Janoušek, Oto (advisor)
Bachelor thesis deals with the analysis of heart rate variability (HRV). By focusing on the analysis of HRV in the time domain and mainly using correlation dimension. It is necessary to propose a methodology for evaluating changes in HRV data using these two techniques of analysis and the comparison of the two approaches. Subsequently create an application in MATLAB for analysis of HRV, which is able to evaluate the effect of changes in HRV caused by ischemia. In the last section it is necessary to discuss the results and the comparison of the two approaches to detect changes induced by ischemia.
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Correlates finding of heart rate changes in fMRI data
Jurečková, Kateřina ; Gajdoš, Martin (referee) ; Bartoň, Marek (advisor)
This master’s thesis deals with problematic of correlates finding of heart rate changes in fMRI data. The first part describes principle of fMRI, creation of BOLD signal, data acquisition, their pre-processing and analysis. The next part describes heart rate variability and its impact on fMRI data. The following section is dedicated to pre-processing of heart rate time series to the form, which can be used in correlates finding of heart rate variability and fMRI data with generalized linear model. The process of statistical testing and its result with discussion can be found in the last part of this thesis.
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Processing of Biosignals Using PC
Románek, Jakub ; Šebesta, Vladimír (referee) ; Sigmund, Milan (advisor)
The Bachelor thesis deals biosignal processing on the computer. In this work are given basic types of biological signals of their way to capture and access to a computer. There are selected examples of available sensors and their subsequent storage record. The project analyzes the software environment, Mathcad and followed to process external signals. Finally, there is a method of measuring the heart pulse and its changes with periods in the histogram.
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ECG based atrial fibrillation detection
Plch, Vít ; Kolářová, Jana (referee) ; Ronzhina, Marina (advisor)
This diploma thesis deals with detection of atrial fibrillation from HRV, classification of Poincare map and in the end the divide into two groups, one with detected atrial fibrillation and one not. The result is the decision on which variables are statistically significant for the identification of atrial fibrillations and which are not, and classification of the ECG signals.
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PPG-based analysis of heart rate variability
Zachar, Erik ; Šaclová, Lucie (referee) ; Ronzhina, Marina (advisor)
The Bachelor's thesis is focused on heart rate variability and its analysis using PPG records. This thesis describes, explains and compares methods of measuring heart rate using electrocardiographic (ECG) and photoplethysmographic (PPG) recordings. In the beginning of thesis, the theory of the cardiovascular system, heart rate variability and acquaintance with the measurement of ECG recordings is described. At the end of the theoretical part, the measurement of PPG records is explained with the possibilities of their subsequent processing for HRV analysis. The practical part deals with data acquisition on volunteers, later the design of an algorithm for signal preprocessing, calculation of selected HRV parameters and finally statistical evaluation of success and discussion of results.
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PPG-based analysis of heart rate variability
Zachar, Erik ; Šaclová, Lucie (referee) ; Ronzhina, Marina (advisor)
HRV, PPG, simultaneous measurement, HRV analysis, daily activities, ECG, deviation detection, respiratory curve
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HRV analysis in the context of daily activities
Indrák, Václav ; Smital, Lukáš (referee) ; Novotná, Petra (advisor)
The aim of this bachelors thesis is to measure ECG recordings on voulenteers, and following analysis of HRV from these recordings. It persues the explanation of basic metrics used to evaluate HRV, used both in clinical and scientific practice and their following programming implementation in Matlab environment to achieve the most accurate results possible, which are than assessed.
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ECG based atrial fibrillation detection
Plch, Vít ; Kolářová, Jana (referee) ; Ronzhina, Marina (advisor)
This diploma thesis deals with detection of atrial fibrillation from HRV, classification of Poincare map and in the end the divide into two groups, one with detected atrial fibrillation and one not. The result is the decision on which variables are statistically significant for the identification of atrial fibrillations and which are not, and classification of the ECG signals.
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