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Methods for respiration estimates from ECG signal
Mitrengová, Jana ; Mézl, Martin (referee) ; Králík, Martin (advisor)
The thesis deals with the realization of methods for estimation of the respiratory curve from the ECG signal. The first part of the thesis deals with the anatomy and physiology of the respiratory and cardiovascular system. In this part of the thesis are also described ways of the breathing monitoring. The second part of the thesis is dedicated to the description of individual methods for the ECG derived respiration. The third part deals with the realization of selected methods, application of method algorithms on real data and comparison of resulting respiratory curves with the respiratory signals available from the PhysioNet database. In conclusion, the individual methods are compared with each other.
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ECG and PPG derived respiration estimation
Chmela, Radek ; Smital, Lukáš (referee) ; Králík, Martin (advisor)
This work deals with the estimation of the respiratory curve from ECG and PPG signals. The first part deals with the description and monitoring of electrical activity of the heart, physiology and methodology of respiratory sensing and photoplethysmography. The second part deals with methods of extracting respiratory cycle information from ECG and PPG recordings. The third part deals with the algorithmic implementation and evaluation of individual procedures for estimating the breath curve from both of the above-mentioned signals on records from the web PhysioNet. In the last part, the algorithms are compared and evaluated.
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Breathing Rate Estimation from the ECG and PPG Signals
Blaude, Ondřej ; Němcová, Andrea (referee) ; Kozumplík, Jiří (advisor)
This bachelor’s thesis is focused on breath rate estimation. In this thesis, methods of breath rate estimation from the ECG and PPG signal are described and implemented. In the first two chapters the basics of ECG measurements are described, as well as the measurements of the respiratory system activity and the PPG signal. The third chapter then describes the ECG/PPG-derived respiratory signal estimation methods, later on the breath rate determination. In the fourth chapter, chosen methods are implemented and the created algorithms are applied on real data from the BIDMC database.
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Respiration rate estimation using PPG signal
Machalová, Marie ; Kozumplík, Jiří (referee) ; Králík, Martin (advisor)
The thesis deals with the estimation of breathing rate from the PPG signal. The first part is theoretical, it deals with the anatomy and physiology of the circulatory and respiratory systems. It also focuses on methods of monitoring these systems. Describes the PPG signal, its acquisition methods and methods for estimating the breathing rate. In next section, there is an introduction to the MESA database, which provides the measured PPG signals. The practical part describes the application of the used methods, their results and validation of the BIDMC database.The method with the smallest average deviation is the drift-based extraction method, with a deviation of 0.57 breaths per minute.
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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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Breathing Rate Estimation from the ECG and PPG Signals
Blaude, Ondřej ; Němcová, Andrea (referee) ; Kozumplík, Jiří (advisor)
This bachelor’s thesis is focused on breath rate estimation. In this thesis, methods of breath rate estimation from the ECG and PPG signal are described and implemented. In the first two chapters the basics of ECG measurements are described, as well as the measurements of the respiratory system activity and the PPG signal. The third chapter then describes the ECG/PPG-derived respiratory signal estimation methods, later on the breath rate determination. In the fourth chapter, chosen methods are implemented and the created algorithms are applied on real data from the BIDMC database.
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ECG and PPG derived respiration estimation
Chmela, Radek ; Smital, Lukáš (referee) ; Králík, Martin (advisor)
This work deals with the estimation of the respiratory curve from ECG and PPG signals. The first part deals with the description and monitoring of electrical activity of the heart, physiology and methodology of respiratory sensing and photoplethysmography. The second part deals with methods of extracting respiratory cycle information from ECG and PPG recordings. The third part deals with the algorithmic implementation and evaluation of individual procedures for estimating the breath curve from both of the above-mentioned signals on records from the web PhysioNet. In the last part, the algorithms are compared and evaluated.
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Methods for respiration estimates from ECG signal
Mitrengová, Jana ; Mézl, Martin (referee) ; Králík, Martin (advisor)
The thesis deals with the realization of methods for estimation of the respiratory curve from the ECG signal. The first part of the thesis deals with the anatomy and physiology of the respiratory and cardiovascular system. In this part of the thesis are also described ways of the breathing monitoring. The second part of the thesis is dedicated to the description of individual methods for the ECG derived respiration. The third part deals with the realization of selected methods, application of method algorithms on real data and comparison of resulting respiratory curves with the respiratory signals available from the PhysioNet database. In conclusion, the individual methods are compared with each other.
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