<?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>1405-9940</journal-id>
<journal-title><![CDATA[Archivos de cardiología de México]]></journal-title>
<abbrev-journal-title><![CDATA[Arch. Cardiol. Méx.]]></abbrev-journal-title>
<issn>1405-9940</issn>
<publisher>
<publisher-name><![CDATA[Instituto Nacional de Cardiología Ignacio Chávez]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-99402017000100061</article-id>
<article-id pub-id-type="doi">10.1016/j.acmx.2016.10.005</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Aumento en la efectividad de la identificación de cimas y pies en el pulso fotopletismográfico al reconstruirlo mediante filtrado adaptativo]]></article-title>
<article-title xml:lang="en"><![CDATA[Increase in the effectiveness of identifying peaks and feet of the photoplethysmographic pulse to be reconstructed it using adaptive filtering]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Becerra-Luna]]></surname>
<given-names><![CDATA[Brayans]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Martínez-Memije]]></surname>
<given-names><![CDATA[Raúl]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cartas-Rosado]]></surname>
<given-names><![CDATA[Raúl]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Infante-Vázquez]]></surname>
<given-names><![CDATA[Oscar]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Instituto Nacional de Cardiología Ignacio Chávez Departamento de Instrumentación Electromecánica ]]></institution>
<addr-line><![CDATA[México, D.F. ]]></addr-line>
<country>México</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Consejo Nacional de Ciencia y Tecnología  ]]></institution>
<addr-line><![CDATA[Ciudad de México ]]></addr-line>
<country>México</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2017</year>
</pub-date>
<volume>87</volume>
<numero>1</numero>
<fpage>61</fpage>
<lpage>71</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-99402017000100061&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-99402017000100061&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-99402017000100061&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen:  Objetivo:  Mejorar la identificación de cimas y pies en el pulso fotopletismográfico (PPG, por sus siglas en inglés), deformado por efecto del ruido miocinético, mediante la implementación de un dedal modificado y filtrado adaptativo.  Método:  Se obtuvo el PPG en 10 voluntarios sanos empleando 2 sistemas de fotopletismografía colocados en el dedo índice de cada mano, y registrándolos simultáneamente durante 3 min. Durante el primer minuto de registro, ambas manos estuvieron en reposo, y durante los 2 min posteriores, solo la mano izquierda realizó movimientos cuasi-periódicos para añadir ruido miocinético. Se emplearon 2 metodologías para procesar las señales fuera de línea, en una se usó un filtro con el algoritmo de mínimos cuadrados promediados (LMS, por sus siglas en inglés) y en la otra se hizo un preprocesamiento adicional al filtrado LMS. Ambas metodologías fueron comparadas y la de menor error porcentual en la señal recuperada se utilizó para valorar la mejora en la identificación de cimas y pies del PPG.  Resultados:  El error promedio obtenido fue del 22.94% para la primera metodología, y del 3.72% para la segunda. Los errores en la identificación de cimas y pies antes de filtrar el PPG fueron del 24.26 y 48.39%, respectivamente, una vez filtrados, disminuyeron a 2.02 y 3.77%, respectivamente.  Conclusiones:  El filtrado adaptativo basado en el algoritmo LMS, más una etapa de preprocesamiento, permite atenuar el ruido miocinético en el PPG, y aumentar la efectividad en la identificación de cimas y pies de pulso, que resultan de gran importancia para una valoración médica.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract:  Objective:  To improve the identification of peaks and feet in photoplethysmographic (PPG) pulses deformed by myokinetic noise, through the implementation of a modified fingertip and applying adaptive filtering.  Method:  PPG signals were recordedfrom 10 healthy volunteers using two photoplethysmography systems placed on the index finger of each hand. Recordings lasted three minutes andwere done as follows: during the first minute, both handswere at rest, and for the lasting two minutes only the left hand was allowed to make quasi-periodicmovementsin order to add myokinetic noise. Two methodologies were employed to process the signals off-line. One consisted on using an adaptive filter based onthe Least Mean Square (LMS) algorithm, and the other includeda preprocessing stage in addition to the same LMS filter. Both filtering methods were compared and the one with the lowest error was chosen to assess the improvement in the identification of peaks and feet from PPG pulses.  Results:  Average percentage errorsobtained wereof 22.94% with the first filtering methodology, and 3.72% withthe second one. On identifying peaks and feet from PPG pulsesbefore filtering, error percentages obtained were of 24.26% and 48.39%, respectively, and once filtered error percentageslowered to 2.02% for peaks and 3.77% for feet.  Conclusions:  The attenuation of myokinetic noise in PPG pulses through LMS filtering, plusa preprocessing stage, allows increasingthe effectiveness onthe identification of peaks and feet from PPG pulses, which are of great importance for medical assessment.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Algoritmo de mínimos cuadrados promediado]]></kwd>
<kwd lng="es"><![CDATA[Pulso fotopletismográfico]]></kwd>
<kwd lng="es"><![CDATA[Acelerómetro]]></kwd>
<kwd lng="es"><![CDATA[Filtros adaptativos]]></kwd>
<kwd lng="es"><![CDATA[Artefactos por movimiento]]></kwd>
<kwd lng="en"><![CDATA[Least mean square algorithm]]></kwd>
<kwd lng="en"><![CDATA[Photoplethysmographic pulse signal]]></kwd>
<kwd lng="en"><![CDATA[Accelerometer]]></kwd>
<kwd lng="en"><![CDATA[Adaptive filters]]></kwd>
<kwd lng="en"><![CDATA[Motion artifacts]]></kwd>
</kwd-group>
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