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Mobil system for monitoring of sports activity
Maleňák, Filip ; Čížek, Martin (referee) ; Rozman, Jiří (advisor)
The aim of this master’s thesis is to analyse methods that are used for monitoring athlete’s activities and a description of current technical solutions with a focus on heart rate and respiratory rate monitoring. The presented solution shows the possibilities of using available open source SW and HW technologies and their implementation in the design of an integrated tool for monitoring sports activities with the iOS operating system.
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Influence of autonomic nervous system in the inducibility of atrial fibrillation.
Šrutová, Martina ; Provazník, Ivo (referee) ; Kolářová, Jana (advisor)
Cílem této práce je zjištění změn předcházejícím fibrilaci síní. Pozorována je rovnováha mezi sympatikem a parasympatikem. Do experimentu výzkumného ústavu Cleavlendské kliniky bylo zapojeno šest psů různých ras. Signály EKG byly získány Holterovským 24hodinovým monitorováním. Pomocí 40 vysokofrekvenčních impulsů (TI) byla každých 30 minut vyvolávána AF. Z 24hodinového signálu byly extrahovány kratší epizody. Každá z těchto epizod obsahovala 10 minut předcházejících TI a 3 minuty následující po TI. Desetiminutové epizody byly zpracovány automaticky, byly detekovány QRS komplexy a RR intervaly a vypočteny HRV parametry. Přítomnost a délka trvání AF byly zjištěny manuálně z tříminutových intervalů následujících po TI. Byla-li vyvolána AF o délce trvání kratší než 30 sekund došlo ve srovnání s epizodami bez výskytu AF k významným změnám tří HRV parametrů. HF parametr poklesl pro epizody s výskytem AF. LF parametr byl naopak vyšší v epizodách s AF. Pro AF delší než 30 sekund nebyly významné změny pozorovány. Změny v epizodách s krátkou AF mohly být způsobeny změnami vlivu sympatiku a parasympatiku. Ke vzniku dlouhých AF je pravděpodobně zapotřebí i jiného vlivu, který nemusí nutně souviset s nervovým systémem. K dalším analýzám je zapotřebí většího množství signálů.
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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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Detrended fluctuation analysis for heart rate variability analysis
Šikner, Tomáš ; Ronzhina, Marina (referee) ; Janoušek, Oto (advisor)
Heart rate variability analysis can be used for a diagnosis of the cardiac diseases. The HRV analysis methods are divided into linear and nonlinear methods. Time-domain method is one of the simplest method and belongs to linear methods. Detrended fluctuation analysis DFA is nonlinear method made relatively recently. In this paper, it has been done the comparison of these two methods based on the changes detection in HRV caused by an ischemia.
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Entropy for heart rate variability analysis
Zemánek, Ladislav ; Čmiel, Vratislav (referee) ; Janoušek, Oto (advisor)
The analysis of HRV is an advanced and noninvasive method which is used to investigate the involuntary nervous system. It is also one of the important parameters of its proper function. Heart rate variability can also be analyzed by entropy, which studies the discrepancy of the RR intervals of the HRV signal and thus can be used to diagnose cardiac diseases
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Software for manual delineation of ECG signals
Jež, Radek ; Kozumplík, Jiří (referee) ; Vítek, Martin (advisor)
This thesis deals with evaluation EKG in terms of classification rhythm and analysis HRV. In theoretic part of work are described basics of heart physiology and its usual pathology, basics of electrocardiography, evaluation EKG and standard methods of HRV evaluation. In practical part are described algorithms used in created application. Mainly describes technique of rhythm evaluation, ectopic rhythms and delineation error elimination, data preparing for HRV evaluation, drift removal from DES and HRV evaluation methods. Created program was tested on CSE and MIT- BIH database records. For lack of suitable data and absence of tested data, it wasn’t possible to test all the classification rules of used algorithms. Tested part of program appears reliable and functional.
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Analysis of Heart Rate Variability
Škrtel, Karol ; Kolářová, Jana (referee) ; Provazník, Ivo (advisor)
The project describes the methods useful for observe changes of heart rate in ECG signal. Heart rate variability become (HRV) the conventionally accepted term to describe variations of NN intervals between consecutive heart beats and generally it is function of instantaneous heart rate or NN interval on time. HRV may be evaluated by time domain or frequency domain measures. In Matlab was developed algorithm, realized like function, which counts HRV parameters from ECG signal series. Analysis in time domain adverts to high correlation between statistic and geometric parameters and similarly with signal HRV. Results of frequency domain analysis shows similarity of power spectral density, which was calculated by two different ways (from interpolated and no interpolated signal HRV). Functionality of developed algorithm was verified on each signal. Project results have signification in progress of analysis ECG signal methods with a view to observe pathological changes in heart rate.
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SMV-2012-22: Data processing in cardiology
Jurák, Pavel ; Halámek, Josef ; Vondra, Vlastimil
Contracted research has been focused on data processing in cardiology. It includes specialized analyzes of large polysomnographic records mainly from long-term sleep studies. Research involves advanced techniques for detection and analysis of heart rate, heart depolarization and repolarization and hemodynamic changes during different sleep stages. Detected numerical parameters were further processed and analyzes by different statistical methods
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