<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>2227-1899</journal-id>
<journal-title><![CDATA[Revista Cubana de Ciencias Informáticas]]></journal-title>
<abbrev-journal-title><![CDATA[Rev cuba cienc informat]]></abbrev-journal-title>
<issn>2227-1899</issn>
<publisher>
<publisher-name><![CDATA[Editorial Ediciones Futuro]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2227-18992020000100079</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Baseline wander removal methods for ECG signals: A comparative study]]></article-title>
<article-title xml:lang="es"><![CDATA[Métodos para eliminación de las derivas de línea base en señales de ECG: Estudio comparativo]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Perdigón Romero]]></surname>
<given-names><![CDATA[Francisco]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Vázquez Romaguera]]></surname>
<given-names><![CDATA[Liset]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Fernandes Costa-Filho]]></surname>
<given-names><![CDATA[Cícero Ferreira]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Guimarães Fernandes]]></surname>
<given-names><![CDATA[Marly]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Evangelista Neto]]></surname>
<given-names><![CDATA[João]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Vázquez-Seisdedos]]></surname>
<given-names><![CDATA[Carlos Román]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,École Polytechnique de Montréal  ]]></institution>
<addr-line><![CDATA[ Montreal]]></addr-line>
<country>Canada</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidade Federal do Amazonas Center for R&amp;D in Electronic and Information Technology ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Brazil</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidade Estadual do Amazonas  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Brasil</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Universidad de Oriente Center for Neuroscience Studies, Images and Signals Processing ]]></institution>
<addr-line><![CDATA[ Santiago de Cuba]]></addr-line>
<country>Cuba</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2020</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2020</year>
</pub-date>
<volume>14</volume>
<numero>1</numero>
<fpage>79</fpage>
<lpage>109</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_arttext&amp;pid=S2227-18992020000100079&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_abstract&amp;pid=S2227-18992020000100079&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_pdf&amp;pid=S2227-18992020000100079&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT Cardiovascular diseases are the leading cause of death worldwide, accounting for 17.3 million deaths per year. The electrocardiogram (ECG) is a non-invasive technique widely used for the detection of cardiac diseases. To increase diagnostic sensitivity, ECG is acquired during exercise stress tests or in ambulatory way. Under these acquisition conditions, the ECG is strongly affected by some types of noises, mainly by baseline wander (BLW). In this work, nine methods, widely used, for the elimination of BLW were implemented, which are: interpolation using cubic splines, finite impulse response (FIR) filter, infinite impulse response (IIR) filter, least mean square adaptive filtering, moving-average filter, independent component analysis, interpolation and successive subtraction of median values in RR interval, empirical mode decomposition, and wavelet filtering. For the quantitative evaluation, the following similarity metrics were used: absolute maximum distance, the sum of squares of distances and percentage root-mean-square difference. Several experiments were performed using synthetic ECG signals generated by ECGSYM software, real ECG signals from QT Database, artificial BLW generated by software and real BLW from the Noise Stress Test Database. The best results were obtained by the method based on FIR high-pass filter with a cut-off frequency of 0.67 Hz.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN Las enfermedades cardiovasculares son la principal causa de muerte en el mundo, y representan 17,3 millones de muertes por año. El electrocardiograma (ECG) es una técnica no invasiva ampliamente utilizada para la detección de enfermedades cardíacas. Para aumentar la sensibilidad diagnóstica, el ECG se adquiere durante las pruebas de esfuerzo o de forma ambulatoria. En estas condiciones, el ECG se ve fuertemente afectado por algunos tipos de ruidos, principalmente por las derivas de línea base (BLW). En este trabajo se implementaron nueve métodos ampliamente utilizados para la eliminación de BLW, que son: interpolación utilizando splines cúbicos, filtro de respuesta a impulso finita (FIR), filtro de respuesta a impulso infinita (IIR), filtrado adaptativo de mínimos cuadrados medios, filtro de media móvil, análisis de componentes independientes, interpolación y substracción sucesiva de los valores de la mediana en el intervalo RR, descomposición en modos empíricos y filtrado de wavelets. Para la evaluación cuantitativa, se utilizaron las siguientes métricas de similitud: distancia máxima absoluta, la suma de los cuadrados de las distancias y la diferencia porcentual de la raíz media cuadrática. Se realizaron varios experimentos utilizando: señales de ECG sintéticas generadas por el software ECGSYM, señales de ECG reales de la base de datos QT, BLW artificiales generadas por software y BLW reales de la base de datos &#8220;Noise Stress Test Database&#8221;. Los mejores resultados se obtuvieron mediante el método basado en el filtro FIR paso alto con una frecuencia de corte de 0,67 Hz.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[ECG]]></kwd>
<kwd lng="en"><![CDATA[baseline wander]]></kwd>
<kwd lng="en"><![CDATA[ICA]]></kwd>
<kwd lng="en"><![CDATA[EMD]]></kwd>
<kwd lng="en"><![CDATA[FIR filters.]]></kwd>
<kwd lng="es"><![CDATA[ECG]]></kwd>
<kwd lng="es"><![CDATA[derivas de línea de base]]></kwd>
<kwd lng="es"><![CDATA[ICA]]></kwd>
<kwd lng="es"><![CDATA[EMD]]></kwd>
<kwd lng="es"><![CDATA[filtros FIR]]></kwd>
</kwd-group>
</article-meta>
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