<?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>S2227-18992020000400123</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Representación basada en imágenes para el reconocimiento patrones mioeléctricos ante variabilidad inter-sesiones]]></article-title>
<article-title xml:lang="en"><![CDATA[Image-based representation to myoelectric pattern recognition in the presence of inter-sessions variability]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Díaz-Amador]]></surname>
<given-names><![CDATA[Roberto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[A.Mendoza-Reyes]]></surname>
<given-names><![CDATA[Miguel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ferrer-Riesgo]]></surname>
<given-names><![CDATA[Carlos A.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Central Marta Abreu de Las Villas Departamento de Ciencias de la Computación ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Cuba</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Central Marta Abreu de Las Villas Departamento de Electrónica y Telecomunicaciones ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Cuba</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Central Marta Abreu de Las Villas Centro de Investigaciones en Informática ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Cuba</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2020</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2020</year>
</pub-date>
<volume>14</volume>
<numero>4</numero>
<fpage>123</fpage>
<lpage>133</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_arttext&amp;pid=S2227-18992020000400123&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_abstract&amp;pid=S2227-18992020000400123&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_pdf&amp;pid=S2227-18992020000400123&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN Los sistemas de control mioeléctrico basados &#8203;&#8203;en reconocimiento de patrones son capaces de clasificar adecuadamente la intensión de movimiento a partir de la señal EMG superficial. Sin embargo, estos sistemas presentan variabilidad inter-sesiones mostrado una caída en el rendimiento en la sesiones de prueba respecto a la sesión de entrenamiento. El objetivo de este trabajo es investigar una nueva representación de la señal HD-EMG basada en rasgos de imágenes para mejorar el reconocimiento inter-sesiones. En este trabajo se compara la utilización de rasgos calculados a partir de una representación 2D instantánea que se forma al considerar cada muestra de la señal HD-EMG como un pixel de una imagen con la utilización de rasgos dominio-temporales calculados a partir de cada canal de HD-EMG. Los rasgos en el dominio del tiempo considerados son el valor medio absoluto, el número de cruces por cero, la longitud de la forma de onda y el cambio de signo de la pendiente. Los rasgos a partir de la representación 2D que se consideran son basados en el valor del pixel y basados en la textura. La utilización de los rasgos propuestos mejora en 15 % (p&lt;0.05) la utilización de los rasgos en el dominio del tiempo cuando se utiliza cada una de las sesiones como sesión de entrenamiento y la otra como sesión de prueba. Los resultados sugieren que la utilización de rasgos a partir de la representación 2D propuesta en este trabajo muestra una mayor robustez a la variabilidad inter-sesiones.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT The myoelectric control systems based on pattern recognition are able to adequately classify the movement intention from the surface EMG signal. However, these systems present intersession variability, reporting a drop in performance in the test sessions compared to the training session. The objective of this work is to investigate an alternative representation of the HD-EMG signal based on imaging features to improve inter-session recognition. In this work, we implement features calculated from an instantaneous 2D representation that is formed by considering each sample of the HD-EMG signal as a pixel of an image. This feature set is compared with the use of temporal domain features calculated from each channel of HD-EMG. The time-domain features considered are the absolute mean value, the number of zero crossings, the length of the waveform, and the sign change of the slope. The features from the 2D representation that are considered are based on the pixel value and based on the texture. The proposed features improve by 15% (p &lt;0.05) the use of the time-domain features when each session is used as a training and the other as a test. The results suggest that using features from the 2D representation proposed in this work show greater robustness to inter-session variability.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Control mioeléctrico]]></kwd>
<kwd lng="es"><![CDATA[Procesamiento de imágenes]]></kwd>
<kwd lng="es"><![CDATA[variabilidad inter-sesiones]]></kwd>
<kwd lng="en"><![CDATA[myoelectric control]]></kwd>
<kwd lng="en"><![CDATA[image processing]]></kwd>
<kwd lng="en"><![CDATA[inter-sesion variability]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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