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A análise da variabilidade da frequência cardíaca é um método útil para avaliar o funcionamento anormal do sistema nervoso autônomo e para prever eventos cardíacos em pacientes com insuficiência cardíaca. As medidas da variabilidade da frequência cardíaca por meio de cardiofrequencímetro têm sido validadas em comparação com eletrocardiograma em indivíduos saudáveis, mas não em pacientes com insuficiência cardíaca. Nós exploramos a reprodutibilidade dos índices da variabilidade da frequência cardíaca obtidos por meio de um cardiofrequencímetro (PolarS810i) e um eletrocardiograma portátil (Holter) nas fases de repouso e de recuperação em dois testes da caminhada de seis minutos consecutivos, com 60 minutos de intervalo entre os dois testes em 50 pacientes com insuficiência cardíaca (~59 anos, New York Heart Association classe funcional II, fração de ejeção do ventrículo esquerdo ~35%). A reprodutibilidade das medidas para cada dispositivo foi analisada por meio do t-test pareado ou Wilcoxon signed-rank test. Adicionalmente, nós avaliamos a concordância entre os dois dispositivos na análise dos índices da variabilidade da frequência cardíaca em repouso, durante o teste da caminhada de seis minutos e durante a fase de recuperação por meio do Coeficiente de Correlação e Concordância (CCC) com 95% de intervalo de confiança e gráficos Bland-Altman. O teste-reteste para análise da variabilidade da frequência cardíaca foi reprodutível com o uso de ambos, o Holter e o PolarS810i, no repouso mas não na fase de recuperação. No segundo teste da caminhada de seis minutos, os pacientes apresentaram aumentos significativo do rMSSD e da distância percorrida. A confiabilidade das medidas do PolarS810i foram consideravelmente altas [0,86 < CCC < 0,99) com base nas medidas do Holter nas três fases: em repouso, durante o teste da caminhada de seis minutos e durante a recuperação. A menor concordância [CCC=0,86] entre os dois dispositivos foi observada no pNN50 durante o teste da caminhada de seis minutos e na fase de recuperação. Em conclusão, nosso estudo mostrou boa reprodutibilidade dos índices da variabilidade da frequência cardíaca em repouso em dois consecutivos testes da caminhada de seis minutos utilizando Holter e PolarS810i. Adicionalmente, o PolarS810i produziu índices confiáveis da variabilidade da frequência cardíaca a partir de registros de curta duração e com base nas gravações simultâneas com o Holter nas três fases: em repouso, durante o teste da caminhada de seis minutos e durante a recuperação em pacientes com insuficiência cardíaca / Heart rate variability analysis is a useful method to assess abnormal functioning in the autonomic nervous system and to predict cardiac events in patients with heart failure. Heart rate variability measurements with heart rate monitors have been validated with an electrocardiograph in healthy subjects but not in patients with heart failure. We explored the reproducibility of heart rate variability indexes using a heart rate monitor (Polar S810i) and a portable electrocardiograph (Holter) at rest and at recovery of two consecutive six-min walk tests, 60 minutes apart in 50 heart failure patients (~59 years, New York Heart Association functional class II, left ventricular ejection fraction ~35%). The reproducibility for each device was analysed using a paired t-test or the Wilcoxon signed-rank test. Additionally, we assessed the agreement between the two devices based on the heart rate variability indexes at rest, during the six-min walk test and during recovery using Concordance Correlation Coefficients (CCC), 95% confidence intervals and Bland-Altman plots. The test-retest for the heart rate variability analyses was reproducible using Holter and PolarS810i at rest but not during recovery. In the second six-min walk test, patients showed significant increases in rMSSD and walking distance. The reliability of PolarS810i measurements was remarkably high [0.86 < CCC < 0.99] based on Holter in the three phases: at rest, during six-min walk test and during recovery. The lowest agreement [CCC=0.86] between the two devices was observed in pNN50 during the six-min walk test and recovery. In conclusion, our study showed good reproducibility of heart rate variability indexes at rest in two consecutive six-min walk test using Holter and Polar S810i. Additionally, PolarS810i produced reliable short-term heart rate variability indexes based on Holter simultaneous recordings at rest, during the six-min walk test and during recovery in heart failure patients

This work focuses on a theoretical explanation of heart rhythm disorders and the possibility of their automatic detection using deep learning networks. For the purposes of this work, a total of 6884 10-second ECG recordings with measured eight leads were used. Those recordings were divided into 5 groups according to heart rhythm into a group of records with atrial fibrillation, sinus rhythms, supraventricular rhythms, ventricular rhythms, and the last group consisted of the others records. Individual groups were unbalanced represented and more than 85 % of the total number of data are sinus rhythm group records. The used classification methods served effectively as a record detector of the largest group and the most effective of all was a procedure consisting of a 2D convolutional neural network into which data entered in the form of scalalograms (classification procedure number 3). It achieved results of precision of 91%, recall of 96% and F1-score values of 0.93. On the contrary, when classifying all groups at the same time, there were no such quality results for all groups. The most efficient procedure seems to be a variant composed of PCA on eight input signals with the gain of one output signal, which becomes the input of a 1D convolutional neural network (classification procedure number 5). This procedure achieved the following F1-score values: 1) group of records with atrial fibrillation 0.54, 2) group of sinus rhythms 0.91, 3) group of supraventricular rhythms 0.65, 4) group of ventricular rhythms 0.68, 5) others records 0.65.

Ztrátová komprese signálů EKG je užitečná a v současnosti stále se rozvíjející oblast. Stále se vyvíjí nové a nové kompresní algoritmy. V této oblasti ale chybí standardy pro hodnocení kvality signálu po kompresi. Existuje tedy sice mnoho různých kompresních algoritmů, které ale buď nelze objektivně porovnat vůbec, nebo jen zhruba. V oblasti komprese navíc nikde není popsáno, zda mají na výkon kompresních algoritmů vliv patologie, popřípadě jaký. Tato dizertační práce poskytuje přehled všech nalezených metod pro hodnocení kvality signálů EKG po kompresi. Navíc bylo vytvořeno 10 nových metod. V rámci práce byla provedena analýza všech těchto metod a na základě jejích výsledků bylo doporučeno 12 metod vhodných pro hodnocení kvality signálu EKG po kompresi. Také je zde představen nový kompresní algoritmus „Single-Cycle Fractal-Based (SCyF)“. Algoritmus SCyF je inspirován metodou založenou na fraktálech a využívá jednoho cyklu signálu EKG jako domény. Algoritmus SCyF byl testován na čtyřech různých databázích, přičemž kvalita signálů po kompresi byla vyhodnocena 12 doporučenými metodami. Výsledky byly porovnány s velmi populárním kompresním algoritmem založeným na vlnkové transformaci, který využívá metodu „Set Partitioning in Hierarchical Trees (SPIHT)“. Postup testování zároveň slouží jako příklad, jak by měl vypadat standard hodnocení výkonu kompresních algoritmů. Dále bylo statisticky prokázáno, že existuje rozdíl mezi kompresí fyziologických a patologických signálů. Patologické signály byly komprimovány s nižší efektivitou a kvalitou než signály fyziologické.

Introduction: Antiretroviral Therapy (ARVT) has been related to some elements of Metabolic Syndrome (MS). Likewise, there exists a high prevalence of alterations on the electrocardiogram (ECG) in people with HIV. Objective: Evaluate the association between MS and alterations in the ECG in HIV patients who received ARVT. Methodology: A consecutive non-randomized cross-sectional study was developed in which patients from the Infectious Disease Service of the Arzobispo Loayza National Hospital were evaluated from January 2019 to April 2020. Survey data, clinical history, clinical examination and a 12-lead ECG were performed to each participant. Alterations in the ECG were classified with the Minnesota code. For SM, NCEP-ATP III 2005 criteria was used. Results: 63 patients were included, the mean age was 38,78 years (SD: 9,23). 25 participants presented electrocardiographic alteration, being 24 minor alterations and 5 major alterations. 27 from the 63 patients (42,9%) had MS. Association was found between MS and ECG alterations in the adjusted model by sex, age, smoking, time with HIV, time with ARVT and use of another medication, with a relative prevalence (RP) value of 2,17 (IC=95% 1,21-3,90) (p=0,009). Conclusion: Although association between the presence of MS and ECG alterations in the HIV population was found, due to the low power of the study, it is recommended to manage the results with caution. / Introducción: La Terapia Antirretroviral de Gran Actividad (TARGA) se ha relacionado con elementos del Síndrome Metabólico (SM). Asimismo, existe una alta prevalencia de alteraciones en el electrocardiograma (ECG) en personas con VIH. Objetivo: Evaluar la asociación entre el SM y las alteraciones en el ECG en pacientes VIH que recibieron TARGA. Metodología: Se desarrolló un estudio transversal con muestreo no aleatorio de tipo consecutivo en el que se evaluó a pacientes del Servicio de Infectología del Hospital Nacional Arzobispo Loayza en el período enero 2019 - abril de 2020. Se incluyeron datos de encuesta, historia clínica, examen clínico y un ECG de 12 derivaciones fue realizado a cada participante. Las alteraciones en el ECG se clasificaron con el código de Minnesota y para SM se utilizaron criterios de NCEP-ATP III 2005. Resultados: Un total de 63 pacientes fueron incluidos, cuya edad media fue 38,78 años (DE: 9,23). Asimismo, 25 (39,68%) participantes presentaron alteraciones electrocardiográficas, obteniendo 24 participantes con alteraciones menores y 5 con mayores. La prevalencia de SM fue de 27 de 63 (42,9%). Se halló asociación entre SM y alteración en el ECG con una prevalencia relativa (PR) de: 2,17 (IC=95% 1,21-3,90) (p=0,009) al ajustar por sexo, edad, tabaquismo, tiempo con VIH, tiempo con TARGA y uso de otra medicación. Conclusión: Aunque se halló asociación entre SM y alteraciones en ECG en población VIH, debido a la baja potencia del estudio se recomienda tomar con cautela estos resultados. / Tesis

The thesis deals with possibilities of using wavelet transform in the field of surface electrocardiogram (ECG) signals denoising and ECG signals measuring. Several algorithms have been used to detect and estimate T-wave alternans (TWA), such as spectral method (SM), Poincaré Mapping (PM) or correlation method (CM). T-wave alternans, also called repolarization alternans, is a phenomenon appearing in the electrocardiogram as a consistent fluctuation in the repolarization morphology on every-other-beat basis. Electrical TWA has been recognized as a marker of electrical instability, and has been shown to be related with patients at increased risk for ventricular arrhytmias. Presence of TWA has been reported in a wide range of clinical and experimental situations including long QT syndrome, myocardial infarction, angina pectoris, acute ischemia, etc. Projected methods of detection TWA are realized in Matlab software, and they are experimentally verified on real ECG signals from the European ST-T Database.

The topic of this master's thesis is the analysis of ECG signals using wavelet transform. In the introductory chapters there is a brief description of heart anatomy, the emergence and spread of potentials, which evocating activities of myocardium. There is an overview of techniques used for ECG signals analysis and explanation of ECG curve diagnostic importance. Work also containts an ECG signal analysis common procedure explanation and different approaches brief overview. The main part of this work is an application detecting significant intervals in the ECG signal, developed in Matlab. In several chapters the detection procedure is described in more details and gave reasons for chosen methods. In the last chapter there is a preview of several signals as a result of developed application, together with evaluation of the tests carried out at the CSE database. Detector sensitivity was quantified over 99,10%.

The resume of this master´s thesis is to introduce reader into principal component analysis (PCA), namely, the use of PCA for analysis of ECG. This method allows to reduce quantity of the data without loss of useful information. That is why PCA is widespread for preprocessing of the data for further classification, which this thesis also deals. Data available at the Department of Biomedical Engineering at the University of Technology in Brno were used in this work. All the methods were realized using Matlab.

The aim of this work is to study and describe the principles and method of delineation of ECG signals. Learn and describe about method of cluster analysis. In this work was created and described three different methods of delineations of ECG signals. Created algorithms were tested on complete CSE database. With cluster analysis were combine created methods. The obtained results from realized methods and combined method were compared with others known methods. At the end of this work is evaluate efficiency of detection of combined method.

This master’s thesis deals with methods for detection of myocardial ischemia in the ECG signal. There is explained the principle of spreading of electrical activity through the heart muscle and its manifestations on the ECG. There are also mentioned the causes of myocardial ischemia and various methods of its detection in the ECG signal. In great detail there is explained the process of implementation of the two selected detection methods of myocardial ischemia in MATLAB. These methods are tested on the data from The PTB Diagnostic ECG Database. Finally, there is the presentation of detection results on used data and overall assessment of created algorithms.