Thesis (M.S.)--University of Florida, 2004. / Title from title page of source document. Document formatted into pages; contains 58 pages. Includes vita. Includes bibliographical references.

Thesis (M.S.)--University of Florida, 2004. / Title from title page of source document. Document formatted into pages; contains 81 pages. Includes vita. Includes bibliographical references.

The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Title from PDF of title page (University of Missouri--Columbia, viewed on September 25, 2009). Thesis advisor: Dr. Luis Polo Parada. Includes bibliographical references.

Thesis (M.S.)--West Virginia University, 2000. / Title from document title page. Document formatted into pages; contains vii, 62 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 61-62).

Thesis (M.S.)--University of Texas at Dallas, 2008. / Includes vita. Includes bibliographical references (leaves 34-37)

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Made available in DSpace on 2016-02-05T18:29:43Z (GMT). No. of bitstreams: 0 Previous issue date: 2015-10-08. Added 1 bitstream(s) on 2016-02-05T18:33:44Z : No. of bitstreams: 1 000857500.pdf: 4743253 bytes, checksum: da5d2724b71f588ae56be27cfaf9a5bd (MD5) / O Eletrocardiograma (ECG) e um exame de extrema importância para avaliar a saúde do coração de um individuo. A analise de seu traçado possibilita diagnosticar uma serie de doenças e anomalias. Para isso, sistemas computacionais precisam segmentar os sinais de ECG, cujo primeiro passo e a detecção dos complexos QRS (ondas Q, R e S). Mui- tos métodos tem sido propostos para tal finalidade. Os primeiros utilizavam técnicas de filtragem e diferenciação, mas recentemente alguns pesquisadores tem concebido metodologias baseadas na analise de multirresolução da transformada Wavelet. Seguindo caminho semelhante, neste trabalho e proposta uma metodologia baseada na decomposição em valores singulares em multirresolução (MRSVD), para solução do problema de detecção dos complexos QRS de um sinal de ECG, que pode ser dividida em quatro etapas essenciais: pré-processamento, inspeção, decisão e correção. Em quase todas elas ha implementações inovadoras: na primeira utiliza-se, de forma inédita, a MRSVD; na segunda etapa exploram-se características fisiológicas do músculo cardíaco para certificar-se de que um determinado segmento compreende ou não uma onda R autentica; na ultima, são corrigidas as detecções baseadas nas amplitudes das ondas R. A avaliação da qualidade de detecção, para os experimentos realizados, mostra que o algoritmo proposto atingiu taxa de previsibilidade de 99, 20%, taxa de sensibilidade de 99, 70% e erro de apenas 1,10%, contra 97, 10%, 99, 00% e 3, 70%, respectivamente, obtidas por outro método / The electrocardiogram (ECG) is a test of utmost importance to evaluate the heart health of a person. The analysis of its layout enables diagnose a number of diseases and abnor- malities. For computer systems that need to segment the ECG signal, the first step the detection of QRS complexes. The earliest methods used filtering techniques and differen- tiation. Recently some researchers have designed methodologies based the multiresolution analysis the wavelet transform. Following similar path, this work proposes a methodology based on singular value decomposition in multiresolution (MRSVD), to solve the prob- lem of detection of QRS complexes of an ECG signal, which can be divided in four key stages: preprocessing, inspection, decision and correction. In of all, there are innovative proposals: in the first, it is used, in an unprecedented manner, the MRSVD; the second stage explores the physiological characteristics of the heart muscle, to make sure that a particular segment comprises or not a genuine R wave and, the last, corrects detections based on the amplitudes of the R wave. The evaluation of quality of detection for the experiments shows that the proposed algorithm has reached a predictive and sensitivity rates of of 99.20% and 99.70%, respectively, and error of only 1.10%, in comparation to another method which obtained 97, 10%, 99, 00% and 3, 70%, respectively

Orientador: Jozué Vieira Filho / Banca: Marco Aparecido Queiroz Duarte / Banca: Roberto Kawakami Harrop Galvão / Resumo: O Eletrocardiograma (ECG) e um exame de extrema importância para avaliar a saúde do coração de um individuo. A analise de seu traçado possibilita diagnosticar uma serie de doenças e anomalias. Para isso, sistemas computacionais precisam segmentar os sinais de ECG, cujo primeiro passo e a detecção dos complexos QRS (ondas Q, R e S). Mui- tos métodos tem sido propostos para tal finalidade. Os primeiros utilizavam técnicas de filtragem e diferenciação, mas recentemente alguns pesquisadores tem concebido metodologias baseadas na analise de multirresolução da transformada Wavelet. Seguindo caminho semelhante, neste trabalho e proposta uma metodologia baseada na decomposição em valores singulares em multirresolução (MRSVD), para solução do problema de detecção dos complexos QRS de um sinal de ECG, que pode ser dividida em quatro etapas essenciais: pré-processamento, inspeção, decisão e correção. Em quase todas elas ha implementações inovadoras: na primeira utiliza-se, de forma inédita, a MRSVD; na segunda etapa exploram-se características fisiológicas do músculo cardíaco para certificar-se de que um determinado segmento compreende ou não uma onda R autentica; na ultima, são corrigidas as detecções baseadas nas amplitudes das ondas R. A avaliação da qualidade de detecção, para os experimentos realizados, mostra que o algoritmo proposto atingiu taxa de previsibilidade de 99, 20%, taxa de sensibilidade de 99, 70% e erro de apenas 1,10%, contra 97, 10%, 99, 00% e 3, 70%, respectivamente, obtidas por outro método / Abstract: The electrocardiogram (ECG) is a test of utmost importance to evaluate the heart health of a person. The analysis of its layout enables diagnose a number of diseases and abnor- malities. For computer systems that need to segment the ECG signal, the first step the detection of QRS complexes. The earliest methods used filtering techniques and differen- tiation. Recently some researchers have designed methodologies based the multiresolution analysis the wavelet transform. Following similar path, this work proposes a methodology based on singular value decomposition in multiresolution (MRSVD), to solve the prob- lem of detection of QRS complexes of an ECG signal, which can be divided in four key stages: preprocessing, inspection, decision and correction. In of all, there are innovative proposals: in the first, it is used, in an unprecedented manner, the MRSVD; the second stage explores the physiological characteristics of the heart muscle, to make sure that a particular segment comprises or not a genuine R wave and, the last, corrects detections based on the amplitudes of the R wave. The evaluation of quality of detection for the experiments shows that the proposed algorithm has reached a predictive and sensitivity rates of of 99.20% and 99.70%, respectively, and error of only 1.10%, in comparation to another method which obtained 97, 10%, 99, 00% and 3, 70%, respectively / Mestre

Cardiac arrhythmias occur when the normal pattern of electrical signals in the heart breaks down. A premature ventricular contraction (PVC) is a common type of arrhythmia that occurs when a heartbeat originates from an ectopic focus within the ventricles rather than from the sinus node in the right atrium. This and other arrhythmias are often diagnosed with the help of an electrocardiogram, or ECG, which records the electrical activity of the heart using electrodes placed on the skin. In an ECG signal, a PVC is characterized by both timing and morphological differences from a normal sinus beat. An implantable cardiac monitor (ICM) is a device used to help physicians diagnose and monitor infrequent cardiac arrhythmias that may not be observed during an ECG recording performed during a normal clinic visit. These devices are implanted under the skin of the chest and simply monitor and record the electrical activity of the heart. The recorded signal is referred to as a subcutaneous electrocardiogram, or SECG. This thesis proposes and tests a novel algorithm that uses an SECG signal to perform PVC detection and is suitable for implementation within an implantable cardiac monitoring device. The proposed algorithm uses a combination of morphological and timing criteria to identify PVCs in near real time. Current commercially-available ICMs do not provide a PVC detection feature, so the proposed algorithm could help provide physicians with valuable additional diagnostic information about a clinically-significant arrhythmia.

Dans le problème inverse d’électrocardiographie, le cible est faire la reconstruction de l’activité électrophysiologique dans le cœur sans mesurer directement dans sa surface (sans interventions avec cathéter). Il est important remarque que en l’actualité la solution numérique du problème inverse est résolu avec le modèle quasi-statique. Ce modèle ne considère pas la dynamique du cœur et peut produire des erreurs dans la reconstruction de la solution sur la surface du cœur. Dans cette thèse, différents méthodologies était investigue pour résoudre le problème inverse d’électrocardiographie comme intelligence artificielle, et modèles dynamiques limites. Aussi, les effets de différents opérateurs en utilisant méthodes d’éléments de frontière , et méthodes d’élément finis était investigue. / In the inverse problem of electrocardiography, the target is to make the reconstruction of electrophysiological activity in the heart without measuring directly in its surface (without interventions with catheter). It is important to note that the current numerical solution of the inverse problem is solved with the quasi-static model. This model does not consider the dynamics of the heart and can cause errors in the reconstruction of the solution on the surface of the heart. This thesis investigates different methodologies was to solve the inverse problem of electrocardiography as artificial intelligence and dynamic models limits. Also, the effects of different operators using boundary element methods, finite element methods, and was investigates.