This master’s thesis is engaged in usage of cluster analysis for ECG signal to separate normal QRS complexes from abnormal ones. For this, it is used two algorithms created in professional computing interface MATLAB. The outputs from this master’s thesis are dendrograms, which divide QRS complexes into abnormal and normal clusters, and Pearson correlation coefficients.

This master's thesis deals with an analysis of principles of ECG signals detection and delineation. The theoretical part describes heart electrophysiology and electrocardiography basics. Next, the most important QRS detection and ECG delineation algorithms are introduced. Especially the wavelet transform methods are described. In the practical part proper delineation algoriythm was realized. It was tested on the standard CSE database, then it was modified on data of isolated rabbit heartsand the results are published in the conclusion.

A T wave peak and offset detector based on an unpublished lead transformation that can be briefly described as multilead linear regression was proposed and implemented afterwards. Potential of the transformation as a useful QRS detection tool was revealed later on. Proposed QRS detector was put to the test of CSE database. Results were compared with work of other authors. Results of T wave peak and offset detector were introduced in visual way.

The aim of this diploma thesis is to introduce methods of detection of the QRS complex and the subsequent detection of P waves. The intention is to create a program by specified method in the software Matlab which will be able to implement this method. The thesis describes the basic and important methods of detection and subsequent algorithm to detect P waves. Solution of the algorithm is tested on real data. It also describes the automatic signal evaluation and the results of this automatic function.

This master thesis deals with QRS complex detection and ECG delineation. The theoretical part of this work describes wavelet transform, some of QRS detection approaches and some of ECG delineation approaches. For algorithm realization in Matlab is used redundant dyadic discrete wavelet transform. Algorithm is designed for experimental electrocardiograms of isolated rabbit hearts and it is evaluated through manually determined references.

Abstract Cardiovascular diseases are the leading cause of death in developed countries. Approximately 50% of these events are due to sudden cardiac death (SCD) and often without preceding diagnosis of cardiac disease. Many risk factors for cardiac events have been identified and prevention strategies have improved markedly. The aim of this thesis was to evaluate the usability of the 12-lead electrocardiogram (ECG) to predict cardiac events. The study population consisted of 10,904 middle-aged general population subjects with ECG recordings between the years 1966–1972 with a long follow-up (30±11 years). The first part of the thesis (I) focused on the prevalence and prognostic significance of fragmented QRS complex (fQRS). The prevalence of fQRS was 19.7%. Fragmented QRS complex did not predict mortality in subjects with no history of cardiac disease. Among subjects with underlying cardiac disease and lateral fQRS, the risk of cardiac death was 2.5-fold (P=0.001) and the risk of SCD was almost 3-fold (P=0.004). Other major electrocardiographic abnormalities were assessed in subjects without known cardiac disease for the risk of cardiac death, SCD and hospitalization due to coronary artery disease (II, III). Abnormal ECG was moderately associated with cardiac death after 10 and 30 years of follow-up (hazard ratio 1.7, P=0.009; hazard ratio 1.3, P>0.001, respectively) (II). The risk of hospitalization was not associated with abnormal ECG findings. Abnormal ECG moderately predicted SCD during 10 and 30 years of follow-up (hazard ratio 1.6, P=0.052; hazard ratio 1.3, P=0.007) (III). The risk of SCD was 3-fold when ≥2 ECG abnormalities were present. In conclusion, lateral fQRS in middle-aged subjects with underlying cardiac disease was associated with increased risk of death. Certain abnormal ECG findings associated with the risk of non-arrhythmic cardiac mortality and arrhythmic death. The risk of arrhythmic mortality was substantially elevated when multiple ECG abnormalities were present in middle-aged population. / Tiivistelmä Sydänsairaudet ovat yleisin kuolinsyy kehittyneissä maissa. Noin 50 % näistä kuolemista aiheutuu äkillisestä sydänpysähdyksestä, suuri osa ilman aiempaa tietoa sairaudesta. Useita sydänsairauksien riskitekijöitä on tunnistettu ja ennaltaehkäisy on kehittynyt merkittävästi. Väitöstutkimuksen tavoitteena on tutkia 12-kytkentäisen sydänsähkökäyrän (EKG) käyttökelpoisuutta sydänsairauksien ilmenemisen ennustamisessa. Tutkimusväestöön kuului 10,904 keski-ikäistä suomalaista henkilöä. Aineisto kerättiin vuosina 1966-1972 ja seuranta-aika oli 30 (±11) vuotta. Ensimmäisessä osajulkaisussa (I) tutkimme QRS-kompleksin fragmentaation vallitsevuutta ja sen vaikutusta ennusteeseen väestössä. Fragmentoituneen QRS-kompleksin esiintyvyys oli 19.7 %. Fragmentoitunut QRS-kompleksi ei lisännyt kuolemanriskiä henkilöillä, joilla ei ollut sydänsairautta. Henkilöillä, joilla oli todettu sydänsairaus, lateraalinen fQRS lisäsi sydänperäistä kuolleisuutta 2.5-kertaiseksi (P=0.001) ja rytmihäiriöperäistä kuolleisuutta 3-kertaiseksi (P=0.004). Tutkimme muiden poikkeavien EKG-löydösten ennustearvoa kuolleisuuteen ja sairaalahoidon tarpeeseen sepelvaltimokohtauksen vuoksi (II, III). Poikkeavien EKG-muutosten esiintymiseen liittyi lisääntyneen sydänperäisen kuoleman riski sekä 10 vuoden (riskitiheyssuhde 1.7, P=0.009) että 30 vuoden seurannassa (riskitiheyssuhde 1.3, P>0.001) (II). Poikkeavat EKG-muutokset eivät ennustaneet sairaalahoitojaksoja. Poikkeava EKG ennusti rytmihäiriöperäisen kuoleman riskiä sekä 10 vuoden (riskitiheyssuhde 1.6, P=0.052) että 30 vuoden seurannassa (riskitiheyssuhde 1.3, P=0.007) (III). Äkkikuoleman riski oli 3-kertainen henkilöillä, joilla todettiin ≥ 2 EKG-poikkeavuutta. Tutkimuksen yhteenvetona voidaan todeta, että fQRS lateraalisissa kytkennöissä lisäsi sydänperäisen kuoleman riskiä henkilöillä, joilla on todettu sydänsairaus. Tiettyihin poikkeaviin EKG-muutoksiin liittyi lisääntynyt ei-rytmihäiriöperäisen ja rytmihäiriöperäisen kuoleman riski. Useiden tutkittujen EKG-muutosten ilmentyminen samanaikaisesti lisäsi merkittävästi rytmihäiriöperäisen kuoleman riskiä keski-ikäisessä väestössä.

In this thesis we suggest a technique for detecting pulses by signal processing of a raw ECG signal registered from 4 electrodes located on the left upper arm. The signal processing is performed in Matlab and consists of normalization, lowpass filtering, highpass filtering, derivation, squaring and a moving average window to reduce interference. The technology is capable of extracting periods between heartbeats after an implemented detection algorithm. The thesis also includes reflections on the types of interferences that may affect an electrical development equipment and also methods of how major parts of the interference can be reduced by different shields. Before the technique is applied in a final product, further tests may need to be performed during the monitoring of a person's pulse. Finally, we believe that our development of pulse detection is the beginning of a new technology that in the future can save lives. / I den här rapporten föreslår vi en teknik för att detektera pulser med hjälp av att signalbehandla en rå EKG-signal registrerad från 4 elektroder placerade på vänster överarm. En signalbehandling utförd i Matlab som bland annat består av normering, lågpassfiltrering, högpassfiltrering, derivering, kvadrering samt ett glidande medelvärdesfönster för att reducera störningar. Tekniken är kapabel till att utvinna tider mellan hjärtslag efter en implementerad detekteringsalgoritm. Rapporten innefattar även reflektioner kring vilka typer av störningar som kan påverka en elektrisk utvecklingsutrustning samt metoder för hur större delar av störningarna kan reduceras med hjälp av olika skärmningar. Innan tekniken appliceras i en slutlig produkt kan ytterligare tester behöva utföras under monitorering av en persons puls. Slutligen anser vi att våran utveckling av pulsdetektion är en början på en ny teknik för att kunna rädda liv.

The Cardiac Rhythm Management Division of St. Jude Medical specializes in the development of implantable cardioverter defibrillators that improve the quality of life for patients diagnosed with a variety of cardiac arrhythmias, especially for patients prone to sudden cardiac death. With the goal to improve detection of cardiac arrhythmias, this study explored the value in time-frequency analysis of intracardiac electrogram in four steps. The first two steps characterized, in the frequency domain, the waveforms that construct the cardiac cycle. The third step developed a new algorithm that putatively provides the least computationally expensive way to identifying cardiac waveforms in the frequency domain. Lastly, this novel approach to analyzing intracardiac electrogram was compared to a threshold crossing algorithm that strictly operates in the time domain and that is currently utilized by St. Jude Medical. The new algorithm demonstrated an equally effective method in identifying the QRS complex on the ventricular channel. The next steps in pursing time-frequency analysis of intracardiac electrogram include implementing the new algorithm on a testing platform that emulates the latest implantable cardioverter defibrillator manufactured by St. Jude Medical and pursuing a similar algorithm that can be employed on the atrial channel.

Made available in DSpace on 2016-03-15T19:37:40Z (GMT). No. of bitstreams: 1 Luiz Carlos Ferreira Rodrigues.pdf: 3281430 bytes, checksum: ce62f748aa1e8330c7d6402e06d3d41f (MD5) Previous issue date: 2012-03-02 / The cardiopathies are currently, according the Ministério da Saúde, the second biggest cause of mortality among the Brazilians, behind only the brain vascular diseases. The motivation for the work here presented is the identification and classification of cardiopathies registered in Electrocardiogram exams, ECG, such as premature contractions, branches blocks, tachycardia and other rhythms disturbance. Due its easy application and low cost, the ECG is one of the resources more commonly used by researchers and health professionals in the assessment of cardiac conditions. The computational application developed in this study relies in the application of Wavelets Transforms for the digital signal processing of ECG, in extracting the morphologic characteristics, dynamics and spectral of the cycles of the signal and in the submission of these characteristics to two Support Vector Machines (SVM). The output of these two SVM's are combined as input to a Bayesian Network for the identification and classification of the cardiopathies. The characteristic of each cycle, morphologic and spectral, has it dimensionality reduced by Principal Component Analysis (PCA). The spectral characteristics are extracted by the extractions of the Wavelets Transforms coefficients of the signal, whilst the dynamics characteristics are defined by the interval between the global maxima of each cycle. For development, testings and validations of the application we utilize the MIT-BIH Arrhythmia database, made available by Massachusetts Institute of Technology (MIT). At the end of this work we demonstrate that the application is able to recognize and classify 8 types of heart beats in ECG records, with an medium accuracy above 95,0%. / As cardiopatias são atualmente, segundo o Ministério da Saúde, a segunda maior causa de mortalidade entre brasileiros, ficando atrás apenas das doenças cerebrovasculares. A motivação do trabalho aqui apresentado é a identificação e classificação de cardiopatias registradas em exames de Eletrocardiograma, o ECG, tais como contrações prematuras, bloqueio de ramos, taquicardias e outros distúrbios de ritmo. Devido a sua fácil aplicação e baixo custo, o ECG é um dos recursos mais largamente utilizados por pesquisadores e profissionais da saúde na avaliação da saúde do coração. A aplicação computacional desenvolvida neste estudo concentra-se no uso de Transformadas Wavelets para o processamento digital dos sinais de ECG, na extração das características morfológicas, dinâmicas e espectrais de ciclos do sinal e na submissão dessas características a duas Máquinas de Vetores de Suporte (SVM). Os resultados das SVM's são combinadas em uma Rede Bayesiana para a identificação e classificação das cardiopatias. As características morfológicas de cada ciclo do sinal são extraídas através de Análise de Componentes Principais (PCA), as características espectrais são extraídas através da decomposição do sinal em coeficientes de Transformadas Wavelets enquanto as características dinâmicas são definidas pelos intervalos entre o máximo global de cada ciclo. Para desenvolvimento, testes e validação da aplicação foi utilizado o Banco de Arritmias MIT-BIH, disponibilizado pelo Massachusetts Institute of Technology (MIT). Neste trabalho demonstramos que a aplicação desenvolvida é capaz de reconhecer e classificar 8 tipos de batimentos cardíacos em registros de ECG, com uma acurácia média total de classificação superior a 95,0%.

Abstract Sudden cardiac death (SCD) is a major medical and public health concern responsible for 50% of cardiovascular deaths and as much as 15% to 20% of overall mortality. Coronary heart disease is the underlying cause of most of these deaths, and in 50% of such cases, SCD is the first manifestation of the disease. Researchers have investigated numerous noninvasive methods to more accurately identify individuals at high risk of SCD, but most such studies have focused on patients with specific heart disease. The standard 12-lead electrocardiogram (ECG) is a widely available tool to analyze the electrical activity of the heart, but few epidemiological studies have successfully identified specific electrocardiographic risk markers of SCD at the population level. This thesis aims to clarify the prognostic implications of several ECG patterns in the general population. We evaluated the 12-lead ECGs of 10899 middle-aged Finnish subjects (52% male) recorded between 1966 and 1972, and followed the subjects for 30 ±  11 years. The prevalence of a prolonged QRS duration ≥ 110 ms and nonspecific intraventricular conduction delay (IVCD; defined as QRS ≥ 110 ms with no partial or complete bundle branch block) in the population was 1.3% and 0.6%, respectively. Both were significantly associated with an elevated risk of all-cause mortality and cardiovascular mortality. QRS duration ≥ 110 ms doubled the risk of SCD, and IVCD was associated with a three-fold higher risk of SCD. Two percent of the subjects presented with wide frontal QRS-T angle ≥ 100° (the angle between the QRS axis and the T-wave axis in the frontal plane). A wide QRS-T angle was associated with higher overall mortality and more than doubled the risk of SCD, which was mainly due to an abnormal T-wave axis. Inverted T-waves in the right precordial leads (V1–V3) or beyond were present in 0.5% of the population. No increase in mortality or SCD was associated with right precordial T-wave inversions. In contrast, inverted T-waves in other leads than V1–V3 were associated with higher risk of cardiovascular mortality and SCD. Altogether 2.1% of the study participants presented with a prolonged PR interval > 200 ms. No rise in overall mortality, SCD, or hospitalizations due to heart failure, atrial fibrillation, or stroke was observed among these subjects during the follow-up period. In conclusion, of the electrocardiographic parameters studied, prolonged QRS duration, IVCD, and wide QRS-T angle are associated with SCD in the general population, and such changes in an ECG should therefore alert the physician to more closely evaluate and follow the patient. On the other hand, a prolonged PR interval and right precordial T-wave inversions seem to have no prognostic implications in the absence of other features suggestive of underlying heart disease. / Tiivistelmä Sydänperäinen äkkikuolema on yleisin kuolinsyy länsimaissa, missä puolet sydänkuolemista ja 15–20 % kokonaiskuolleisuudesta johtuu äkillisestä sydänpysähdyksestä. Sepelvaltimotauti on yleisin taustalla oleva syy, ja jopa puolessa sepelvaltimotautikuolemista äkkikuolema on taudin ensimmäinen oire. Jo pitkään on yritetty kehittää menetelmiä, joilla voitaisiin tunnistaa suurimmassa äkkikuoleman vaarassa olevat. 12-kanavainen EKG on laajalti käytössä oleva tutkimus, jolla tutkitaan sydämen sähköistä toimintaa, mutta sydänperäistä äkkikuolemaa spesifisti väestössä ennustavia EKG-poikkeavuuksia ei ole juuri pystytty osoittamaan. Tämän väitöskirjatyön tarkoituksena oli tutkia, miten EKG:ssä nähtävät ilmiöt kuten QRS kompleksin kesto, QRS-kompleksin ja T-aallon välinen kulma, kääntyneet T-aallot sekä PR-aika korreloivat ennusteeseen väestötasolla. Tutkimme 10899 suomalaisen keski-ikäisen henkilön (52 % miehiä) EKG:t, jotka oli rekisteröity 1966–1972, ja seurasimme tutkittavia keskimäärin 30 (± 11) vuotta. Leventynyt QRS kompleksi ≥ 110 ms löytyi 1.3 %:lta ja epäspesifi kammionsisäinen johtumishäiriö eli IVCD (QRS ≥ 110 ms ilman osittaista tai täydellistä haarakatkosta) 0.6 %:lta tutkituista. Molemmat muutokset liittyivät lisääntyneeseen kokonaiskuolleisuuteen sekä sydänkuoleman riskiin. QRS kompleksin kesto ≥ 110 ms assosioitui lisäksi kaksinkertaiseen ja IVCD kolminkertaiseen äkkikuolemariskiin. 2 %:lla tutkituista sydänlihaksen depolarisaation suuntaa kuvaavan QRS-kompleksin akselin ja repolarisaatiota kuvaavan T-aallon akselin välinen frontaalitason QRS-T kulma oli leveä ≥ 100°. Näillä henkilöillä kokonaiskuolleisuus oli lisääntynyt, ja sydänperäisen äkkikuoleman riski oli yli kaksinkertainen verrattuna henkilöihin jolla QRS-T kulma oli  < 100°. Oikeanpuoleisissa rintakytkennöissä V1–V3 todettiin negatiiviset T-aallot 0.5 %:lla tutkituista, mutta näillä ei ollut vaikutusta kuolleisuuteen. Sen sijaan henkilöillä, joilla todettiin negatiiviset T-aallot muissa kytkennöissä, oli yli kaksinkertainen sydänkuoleman ja äkillisen sydänpysähdyksen vaara muihin tutkittuihin verrattuna. Osallistujista 2.1 %:lla todettiin pidentynyt PR-aika > 200 ms. Tämä ei kuitenkaan vaikuttanut henkilöiden kuolleisuuteen eikä sydämen vajaatoiminnasta, eteisvärinästä tai aivoverenkiertohäiriöistä johtuvien sairaalahoitojen määrään. Tutkituista EKG:n poikkeavuuksista siis pidentynyt QRS-kompleksin kesto, IVCD ja leveä QRS-T kulma liittyvät selvästi lisääntyneeseen äkillisen sydänpysähdyksen riskiin. Sen sijaan pidentynyt PR-aika tai T-inversiot oikeanpuoleisissa rintakytkennöissä ilman muuta viitettä sydänsairaudesta eivät vaikuta ennusteeseen keski-ikäisessä väestössä.