<?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>1815-5928</journal-id>
<journal-title><![CDATA[Ingeniería Electrónica, Automática y Comunicaciones]]></journal-title>
<abbrev-journal-title><![CDATA[EAC]]></abbrev-journal-title>
<issn>1815-5928</issn>
<publisher>
<publisher-name><![CDATA[Universidad Tecnológica de La Habana José Antonio Echeverría, Cujae]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1815-59282023000100058</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Evaluación de un algoritmo para detección de caídas basado en umbrales a partir de señales inerciales]]></article-title>
<article-title xml:lang="en"><![CDATA[Evaluation of an algorithm for threshold-based fall detection from inertial signals.]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Carbó Pérez]]></surname>
<given-names><![CDATA[Alain J.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Salvador Figueroa]]></surname>
<given-names><![CDATA[Elizabeth]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[López Delis]]></surname>
<given-names><![CDATA[Alberto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Centro de Biofísica Médica  ]]></institution>
<addr-line><![CDATA[Santiago de Cuba ]]></addr-line>
<country>Cuba</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>04</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>04</month>
<year>2023</year>
</pub-date>
<volume>44</volume>
<numero>1</numero>
<fpage>58</fpage>
<lpage>65</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_arttext&amp;pid=S1815-59282023000100058&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_abstract&amp;pid=S1815-59282023000100058&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_pdf&amp;pid=S1815-59282023000100058&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen Teniendo en cuenta el desafío del envejecimiento poblacional y el importante problema de salud que representan las caídas entre la población adulta mayor, propiciando limitaciones en las actividades de la vida diaria (AVD) de este sector de la población. El desarrollo de la internet médica de las cosas, los sensores inalámbricos y las unidades de medición inercial (UMI) permiten sensar de manera directa y óptima datos de pacientes en su ámbito natural sin invadir su privacidad. El propósito de este estudio es verificar si mediante un algoritmo de detección de caídas basado en umbrales es posible distinguir con precisión entre personas mayores caídas y personas mayores que desarrollan AVD, a partir del análisis de las variables de aceleración lineal y velocidad angular obtenidas del sensor UMI, empleadas en el cálculo de la magnitud del vector suma (MVS) de la aceleración y velocidad angular, así como en el ángulo de cabeceo y de balanceo. Para así validar una versión piloto de un protocolo experimental para detección de caídas en sujetos sanos en el Centro de Biofísica Médica (CBM). Se evaluó el rendimiento del algoritmo implementándolo en la base de datos pública CGU-BES Dataset, obteniéndose una sensibilidad de un 91.6%, una especificidad de 88.3% y una precisión de 89.4%.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The aging of the population and the significant health problem represented by falls in the elderly population, promotes a growth in the limitations of the activities of daily living (ADL) of this sector of the population. The development of the medical internet of things, wireless sensors and inertial measurement units (IMU) make it possible to directly and optimally sense patient data in their natural environment without invading their privacy. The purpose of this study is to verify if, through a threshold-based fall detection algorithm, it is possible to accurately distinguish between older people, falls, and the development of ADL, based on the analysis of the linear acceleration and angular velocity variables obtained of the UMI sensor. This information is used to calculate the magnitude of the vector sum (SVM) of the acceleration and angular velocity, as well as the pitch and roll angles. Based on this information, a pilot version of an experimental protocol for the detection of falls in healthy subjects was carried out at the Center of Medical Biophysics. The performance of the algorithm was evaluated by implementing it in the public database CGU-BES Dataset, obtaining a sensitivity of 91.6%, a specificity of 88.3% and an accuracy of 89.4%.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[detección de caídas]]></kwd>
<kwd lng="es"><![CDATA[unidad de medición inercial]]></kwd>
<kwd lng="es"><![CDATA[sensores inalámbricos]]></kwd>
<kwd lng="es"><![CDATA[métodos basados en umbrales]]></kwd>
<kwd lng="es"><![CDATA[actividades de la vida diaria]]></kwd>
<kwd lng="en"><![CDATA[fall detection]]></kwd>
<kwd lng="en"><![CDATA[inertial measurement unit]]></kwd>
<kwd lng="en"><![CDATA[wireless sensors]]></kwd>
<kwd lng="en"><![CDATA[threshold-based methods]]></kwd>
<kwd lng="en"><![CDATA[activities of daily living]]></kwd>
</kwd-group>
</article-meta>
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