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      Translated title: Evaluación de tres algoritmos de segmentación del intervalo RT

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          Abstract

          En este trabajo se evalúan tres algoritmos de segmentación automática del intervalo RT. Estos algoritmos son: el algoritmo basado en un filtro derivador, el algoritmo basado en la descomposición de ondículas y el algoritmo basado en la modelización de la onda T. La evaluación se efectuó sobre señales electrocardiográficas sintéticas y reales. En la primera evaluación se contaminó un electrocardiograma (ECG) sintético con cuatro tipos de ruido en cuadro condiciones de Relación Señal a Ruido (SNR) (10, 15, 20 y 25 dB), en la segunda evaluación se compararon los resultados arrojados por los algoritmos con las anotaciones de dos expertos. Los resultados obtenidos muestran comportamientos satisfactorios de los tres enfoques en condiciones favorables de SNR. Sin embargo se observó un aumento de la variabilidad del intervalo RT inducida por el ruido.

          Translated abstract

          Three automatics methods for the extraction of RT intervals are compared: the algorithm based on a derivate filter, the algorithm based on wavelets decomposition and the algorithm based on T wave modelization. The evaluation was carried on computer-generated and on real ECG signals. In the first evaluation, a synthetic electrocardiogram was contaminated with four types of noise in four conditions of Signal to Noise Ratio (SNR) (10, 15, 20 and 25 dB), in the second evaluation the algorithm’s results were compared with the annotations of two experts. The achieved performance shows a satisfying behavior of these approaches in favorable conditions of SNR. Nevertheless an increase of RT beat-to-beat variability induced by the artifacts was observed.

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          Performance assessment of standard algorithms for dynamic R-T interval measurement: comparison between R-Tapex and R-T(end) approach.

          Three automatic approaches to ventricular repolarisation duration measurement (R-Tapex, R-T(end threshold) and R-T(end fitting) methods) are compared on computer-generated and real ECG signals, in relation to their reliability in the presence of the most common electrocardiographic artefacts (i.e. additive broadband noise and additive and multiplicative periodical disturbances). Simulations permit the evaluation of the amount of R-T beat-to-beat variability induced by the artefacts. The R-T(end threshold) method performs better than the R-T(end fitting) one, and, hence, the latter should be used with caution when R-T(end) variability is addressed. Whereas the R-Tapex method is more robust with regard to broadband noise than the R-T(end threshold) one, the reverse situation is observed in the presence of periodical amplitude modulations. A high level of broadband noise dose not prevent the detection of the central frequency of underlying R-T periodical changes. Comparison between the power spectra of the beat-to-beat R-T variability series obtained from three orthogonal ECG leads (X,Y,Z) is used to assess the amount of real and artefactual variability in 13 normal subjects at rest. The R-Tapex series displays rhythms at high frequency (HF) with a percentage power on the Z lead (57.1 +/- 4.9) greater than that on the X and Y leads (41.9 +/- 4.6 and 46.1 +/- 4.9, respectively), probably because of respiratory-related artefacts affecting the Z lead more remarkably. More uniform HF power distributions over X,Y,Z leads are observed in the R-T(end threshold) series (31.8 +/- 3.8, 39.2 +/- 4.1 and 35.1 +/- 4.2, respectively), thus suggesting minor sensitivity of the R-T(end threshold) measure to respiratory-related artefacts.
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            A new approach for TU complex characterization.

            In this paper, we present a new TU complex detection and characterization algorithm that consists of two stages; the first is a mathematical modeling of the electrocardiographic segment after QRS complex; the second uses classic threshold comparison techniques, over the signal and its first and second derivatives, to determine the significant points of each wave. Later, both T and U waves are morphologically classified. Amongst the principal innovations of this algorithm is the inclusion of U-wave characterization and a mathematical modeling stage, that avoids many of the problems of classic techniques when there is a low signal-to-noise ratio or when wave morphology is atypical. The results of the algorithm validation with the recently appeared QT database are also shown. For T waves these results are better when compared to other existing algorithms. U-wave results cannot be contrasted with other algorithms as, to our knowledge, none are available. Examples showing the causes of principal discrepancies between our algorithm and the QT database annotations are also given, and some ways of attempting to improve and benefit from the proposed algorithm are suggested.
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              Comparison of SVD methods to extract the foetal electrocardiogram from cutaneous electrode signals.

              The paper presents and compares three methods making use of the singular value decomposition (SVD) of a matrix to extract the foetal electrocardiogram (FECG) from cutaneously recorded electrode signals. The first method constructs a set of orthogonal foetal signals (the so-called principal foetal signals) from the recordings, but needs electrode positions far from the foetal heart, in addition to the abdominal electrodes that pick up a mixture of maternal and foetal electrocardiogram. An online adaptive algorithm has been developed such that a real-time implementation becomes feasible. The second method is a new online approach to a technique presented by van Oosterom. Although this method has some important drawbacks and is suboptimal as far as foetal signal-to-noise ratio is concerned, it is still very useful when only a foetal trigger is required, as the signal obtained is not a complete FECG. Finally, a third method is proposed, based on the generalised SVD and interpreted with the new concept of oriented signal-to-signal ratio. An online version is also presented for this method and some results are shown.
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                Author and article information

                Journal
                uct
                Universidad, Ciencia y Tecnología
                uct
                Universidad Nacional Experimental Politécnica " Antonio José de Sucre", UNEXPO, Vicerrectorado Puerto Ordaz. (Puerto Ordaz, Bolívar, Venezuela )
                1316-4821
                January 2008
                : 12
                : 46
                : 05-12
                Affiliations
                [01] Caracas orgnameUniversidad Simón Bolívar orgdiv1Dpto. de Electrónica y Circuitos orgdiv2Grupo de Bioingeniería y Biofísica Aplicada Venezuela swong@ 123456usb.ve
                [05] Caracas orgnameUniversidad Simón Bolívar orgdiv1Dpto. de Computación y Tecnología de la Información orgdiv2Grupo de Bioingeniería y Biofísica Aplicada Venezuela alacruz@ 123456ldc.usb.ve
                [02] orgnameUniversidad Simón Bolívar orgdiv1Dpto. de Electrónica y Circuitos orgdiv2Grupo de Bioingeniería y Biofísica Aplicada jcsistemas2001@ 123456gmail.com
                [04] Francia orgnameUniversité de Reines orgdiv1IUT de Rennes alfredo.hernandez@ 123456univ-rennes1.fr.
                [03] Francia orgnameUniversité de Reines orgdiv1IUT de Rennes herve.gauvrit@ 123456univ-rennes1.fr.
                Article
                S1316-48212008000100002 S1316-4821(08)01204602
                c6b96230-3317-44f6-bfa6-60068325c103

                http://creativecommons.org/licenses/by/4.0/

                History
                : 07 November 2007
                : 20 January 2008
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 14, Pages: 8
                Product

                SciELO Venezuela

                Categories
                Bioingeniería

                T Wave,Procesamiento de señales,Onda T,Intervalo RT,ECG,Algoritmos de segmentación,Signal Processing,Algorithms,Segmentation,RT Interval

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