<?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>1405-5546</journal-id>
<journal-title><![CDATA[Computación y Sistemas]]></journal-title>
<abbrev-journal-title><![CDATA[Comp. y Sist.]]></abbrev-journal-title>
<issn>1405-5546</issn>
<publisher>
<publisher-name><![CDATA[Instituto Politécnico Nacional, Centro de Investigación en Computación]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-55462023000100107</article-id>
<article-id pub-id-type="doi">10.13053/cys-27-1-4417</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Estimulación visual basada en conceptos y su análisis mediante electroencefalografía]]></article-title>
<article-title xml:lang="en"><![CDATA[Concept-Based Visual Stimulation and its Analysis by Electroencephalography]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cerino]]></surname>
<given-names><![CDATA[Rigoberto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pinto]]></surname>
<given-names><![CDATA[David]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Vergara]]></surname>
<given-names><![CDATA[Sergio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pérez-Téllez]]></surname>
<given-names><![CDATA[Fernando]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Benemérita Universidad Autónoma de Puebla Facultad de Ciencias de la Computación ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Benemérita Universidad Autónoma de Puebla Facultad de Ciencias de la Electrónica ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Technological University Dublin Faculty of Computing, Digital and Data ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Ireland</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2023</year>
</pub-date>
<volume>27</volume>
<numero>1</numero>
<fpage>107</fpage>
<lpage>126</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-55462023000100107&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-55462023000100107&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-55462023000100107&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: Este artículo está orientado hacia la verificación del rendimiento de un algoritmo computacional capaz de identificar de manera automática las características o rasgos discriminantes que generan las ondas cerebrales utilizando lecturas electroencefalográficas (EEG), cuando el ser humano percibe conceptos a través de un conjunto de estímulos visuales, los cuales están relacionados con el proceso de comunicación humana. Se realiza una comparativa y estudio de los trabajos existentes en la literatura relacionados al tema expuesto, y las limitantes encontradas en las investigaciones actuales. Se desarrolla una metodología para el tratamiento de las señales EEG, se realiza el preprocesamiento de las señales a través de la implementación de un filtro digital preciso y eficiente tipo FIR de orden 4 para eliminar el ruido de las señales. Se implementa el método de Análisis de Componente Independientes (ICA por sus siglas en inglés) para la eliminación de artefactos presentes en las señales, y posteriormente se dividen en épocas para analizar su comportamiento a través de potenciales relacionados con eventos (ERP). Finalmente se analizan las señales que generan distintos conceptos presentados a través de pictogramas y se reportan las observaciones, donde se denota que el algoritmo desarrollado es funcional para la extracción de parámetros para las diferentes categorías de conceptos.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: This article is oriented towards verifying the performance of a computational algorithm capable of automatically identifying the discriminating characteristics or traits generated by brain waves using electroencephalographic (EEG) readings, when the human being perceives concepts through a set of visual stimuli, which are related to the process of human communication. A comparison and study of the existing works in the literature related to the subject exposed, and the limitations found in current research are carried out. A methodology for the treatment of EEG signals is developed, the preprocessing of the signals is carried out through the implementation of a precise and efficient digital filter type FIR of order 4 to eliminate signal noise. The Independent Component Analysis (ICA) method is implemented for the elimination of artifacts present in the signals, and later they are divided into epochs to analyze their behavior through event-related potentials (ERP). Finally, the signals that generate different concepts presented through pictograms are analyzed and the observations are reported, where it is denoted that the algorithm developed is functional for the extraction of parameters for the different categories of concepts.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[EEG]]></kwd>
<kwd lng="es"><![CDATA[ERP]]></kwd>
<kwd lng="es"><![CDATA[análisis]]></kwd>
<kwd lng="en"><![CDATA[EEG]]></kwd>
<kwd lng="en"><![CDATA[ERP]]></kwd>
<kwd lng="en"><![CDATA[analysis]]></kwd>
</kwd-group>
</article-meta>
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