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dc.contributor.authorTello Urrea, Andrés Felipe
dc.coverage.spatialColombia
dc.date.accessioned2022-02-01T15:34:29Z
dc.date.available2121-01-31
dc.date.available2022-02-01T15:34:29Z
dc.date.issued2021
dc.identifier.urihttps://repositorio.escuelaing.edu.co/handle/001/1971
dc.descriptionCaracterización de señales Inerciales y Electromiográficas para fatiga física estimación en ejercicio anaeróbicospa
dc.description.abstractIntroduction: According to the World Health Organization, Cardiovascular diseases are the most significant non-communicable diseases worldwide level, with approximately 17.9 million deaths per year. To decrease the impact after a cardiovascular episode, cardiac rehabilitation is a Class I recommendation. However, to achieve a successful cardiac rehabilitation program, it is important to measure a variety of parameters that can facilitate data analysis and interpretation of the effort performed. Providing experts with relevant data about the patient allows them to guide a safe and optimized rehabilitation process. Objective: The continuous monitoring of physical fatigue during cardiac rehabilitation leads to a safer protocol. However, there is a lack of objective and non-invasive measures for this parameter, mainly, in protocols based on high-intensity exercise. The main purpose of this study was the characterization of relevant features for fatigue detection, obtained from objective measurements such as inertial and electromyographic signals. Methodology: In the experimental process, 21 healthy subjects performed Highintensity interval training to record kinematic, electromyography (EMG), and Borg scale data, the data was obtained from the biceps femoral and gastrocnemius muscles. From the feature extraction, the data were classified based on the Borg scale and compared between fatigue levels. Results: It was observed that most of the features obtained indicate a relationship with fatigue. As expected some features had a better differentiation between fatigue levels. However, despite that the results showed a correlation with the knowledge obtained from the state of the art, the behavior of the mean frequency from the electromyography signal was the opposite of the data reported. Conclusions: It was concluded that the features extracted were representative of the differentiation of three fatigue levels and new insights of the fatigue characterization during high-intensity exercise was obtained. However, more investigations are imperative to corroborate the results, additionally, a clinical environment with cardiac rehabilitation patients is still needed.eng
dc.description.abstractIntroducción: Según la Organización Mundial de la Salud, las enfermedades cardiovasculares son las enfermedades no transmisibles más importantes a nivel mundial, con aproximadamente 17,9 millones de muertes al año. Para disminuir el impacto después de un episodio cardiovascular, la rehabilitación cardíaca es una recomendación de Clase I. Sin embargo, para lograr un programa de rehabilitación cardíaca exitoso, es importante medir una variedad de parámetros que pueden facilitar el análisis de datos y la interpretación del esfuerzo realizado. Proporcionar a los expertos datos relevantes sobre el paciente les permite guiar un proceso de rehabilitación seguro y optimizado. Objetivo: La monitorización continua de la fatiga física durante la rehabilitación cardiaca conduce a un protocolo más seguro. Sin embargo, faltan medidas objetivas y no invasivas de este parámetro, principalmente, en protocolos basados ​​en ejercicio de alta intensidad. El objetivo principal de este estudio fue la caracterización de características relevantes para la detección de fatiga, obtenidas a partir de medidas objetivas como señales inerciales y electromiográficas. Metodología: En el proceso experimental, 21 sujetos sanos realizaron entrenamiento interválico de alta intensidad para registrar datos cinemáticos, electromiográficos (EMG) y escala de Borg, los datos se obtuvieron de los músculos bíceps femoral y gastrocnemio. A partir de la extracción de características, los datos se clasificaron según la escala de Borg y se compararon entre los niveles de fatiga. Resultados: Se observó que la mayoría de las características obtenidas indican relación con la fatiga. Como era de esperar, algunas características tenían una mejor diferenciación entre los niveles de fatiga. Sin embargo, a pesar de que los resultados mostraron una correlación con el conocimiento obtenido del estado del arte, el comportamiento de la frecuencia media de la señal de electromiografía fue contrario a los datos reportados. Conclusiones: Se concluyó que las características extraídas eran representativas de la diferenciación de tres niveles de fatiga y se obtuvieron nuevos conocimientos sobre la caracterización de la fatiga durante el ejercicio de alta intensidad. Sin embargo, más investigaciones son imperativas para corroborar los resultados, además, aún se necesita un entorno clínico con pacientes en rehabilitación cardíaca.spa
dc.format.extent25 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.titleCharacterization of Inertial and Electromyographic signals for physical fatigue estimation in anaerobic exerciseeng
dc.title.alternativeCaracterización de señales Inerciales y Electromiográficas para fatiga física estimación en ejercicio anaeróbicoeng
dc.typeDocumento de trabajospa
dc.type.versioninfo:eu-repo/semantics/publishedVersionspa
oaire.accessrightshttp://purl.org/coar/access_right/c_16ecspa
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.contributor.corporatenameEscuela Colombiana de Ingeniería Julio Garavitospa
dc.contributor.corporatenameUniversidad del Rosariospa
dc.contributor.datamanagerMunera Ramirez, Marcela Cristina
dc.contributor.datamanagerCifuentes García, Carlos Andrés
dc.identifier.urlhttps://catalogo.escuelaing.edu.co/cgi-bin/koha/opac-detail.pl?biblionumber=22866
dc.relation.indexedN/Aspa
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dc.rights.accessrightsinfo:eu-repo/semantics/closedAccessspa
dc.subject.armarcElectromiográficas - señales
dc.subject.armarcFatiga física -Caracterización - Enfermedades Cardio Vasculares
dc.subject.proposalElectromiográficas - señalesspa
dc.subject.proposalFatiga física -Caracterización - Enfermedades Cardio Vascularesspa
dc.subject.proposalPhysical fatigue -Characterization - Cardio Vascular Diseaseseng
dc.subject.proposalElectromyographic - signalseng
dc.type.coarhttp://purl.org/coar/resource_type/c_8042spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/workingPaperspa
dc.type.redcolhttps://purl.org/redcol/resource_type/PICspa


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