Modelo predictivo para el reconocimiento de actividades humanas basado en técnicas de Machine Learning y de selección de características

Ambient assisted living (AAL), focus on generating innovative products and services in order to aid and medical attention to elderly people who suffer from neurodegenerative diseases or a disability. This research area is responsible for the development of activity recognition systems (ARS) which ar...

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Autores:: Patiño Saucedo, Janns Álvaro

Tipo de recurso:

Fecha de publicación:: 2019

Institución:: Corporación Universidad de la Costa

Repositorio:: REDICUC - Repositorio CUC

Idioma:: spa

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repository_id_str
dc.title.spa.fl_str_mv	Modelo predictivo para el reconocimiento de actividades humanas basado en técnicas de Machine Learning y de selección de características
title	Modelo predictivo para el reconocimiento de actividades humanas basado en técnicas de Machine Learning y de selección de características
spellingShingle	Modelo predictivo para el reconocimiento de actividades humanas basado en técnicas de Machine Learning y de selección de características Human Activity Recognition (HAR) Machine learning Classification Feature selection Reconocimiento de Actividades Humanas (HAR) Aprendizaje automático Clasificación Selección de características
title_short	Modelo predictivo para el reconocimiento de actividades humanas basado en técnicas de Machine Learning y de selección de características
title_full	Modelo predictivo para el reconocimiento de actividades humanas basado en técnicas de Machine Learning y de selección de características
title_fullStr	Modelo predictivo para el reconocimiento de actividades humanas basado en técnicas de Machine Learning y de selección de características
title_full_unstemmed	Modelo predictivo para el reconocimiento de actividades humanas basado en técnicas de Machine Learning y de selección de características
title_sort	Modelo predictivo para el reconocimiento de actividades humanas basado en técnicas de Machine Learning y de selección de características
dc.creator.fl_str_mv	Patiño Saucedo, Janns Álvaro
dc.contributor.advisor.spa.fl_str_mv	De-La-Hoz-Franco, Emiro Diaz Martínez, Jorge
dc.contributor.author.spa.fl_str_mv	Patiño Saucedo, Janns Álvaro
dc.subject.eng.fl_str_mv	Human Activity Recognition (HAR) Machine learning Classification Feature selection
topic	Human Activity Recognition (HAR) Machine learning Classification Feature selection Reconocimiento de Actividades Humanas (HAR) Aprendizaje automático Clasificación Selección de características
dc.subject.spa.fl_str_mv	Reconocimiento de Actividades Humanas (HAR) Aprendizaje automático Clasificación Selección de características
description	Ambient assisted living (AAL), focus on generating innovative products and services in order to aid and medical attention to elderly people who suffer from neurodegenerative diseases or a disability. This research area is responsible for the development of activity recognition systems (ARS) which are based on Human Activity Recognition (HAR), specifically in activities of daily life (ADL) in indoor environments. These systems make it possible to identify the type of activity that people carry out, offering a possibility of effective assistance that allows them to carry out daily activities with total normality. The performance of the ARS in the HAR process must be evaluated through the approach of experimental scenarios with data sets available by the scientific community in online repositories, this work proposes a variety of combinations of machine learning algorithms with feature selection algorithms, obtaining as a result a functional model for the HAR, which combines the classification algorithm Logistic model trees (LMT) and the feature selection algorithm One R.
publishDate	2019
dc.date.issued.none.fl_str_mv	2019
dc.date.accessioned.none.fl_str_mv	2021-05-12T18:22:03Z
dc.date.available.none.fl_str_mv	2021-05-12T18:22:03Z
dc.type.spa.fl_str_mv	Trabajo de grado - Maestría
dc.type.content.spa.fl_str_mv	Text
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/masterThesis
dc.type.redcol.spa.fl_str_mv	http://purl.org/redcol/resource_type/TM
dc.type.version.spa.fl_str_mv	info:eu-repo/semantics/acceptedVersion
status_str	acceptedVersion
dc.identifier.uri.spa.fl_str_mv	https://hdl.handle.net/11323/8249
dc.identifier.instname.spa.fl_str_mv	Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv	REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv	https://repositorio.cuc.edu.co/
url	https://hdl.handle.net/11323/8249 https://repositorio.cuc.edu.co/
identifier_str_mv	Corporación Universidad de la Costa REDICUC - Repositorio CUC
dc.language.iso.none.fl_str_mv	spa
language	spa
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Enfermedades neurodegenerativas: MedlinePlus en español. Retrieved January 13, 2020, from Medlineplus website: https://medlineplus.gov/spanish/degenerativenervediseases.html Van Der Malsburg, C. (1986). Frank Rosenblatt: Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms. Brain Theory, (February), 245–248. https://doi.org/10.1007/978-3-642-70911-1_20 Van Kasteren, T. L. M., Englebienne, G., & Kröse, B. J. A. (2010). Activity recognition using semi-Markov models on real world smart home datasets. Journal of Ambient Intelligence and Smart Environments, 2(3), 311–325. https://doi.org/10.3233/AIS-2010-0070 Weiss, S. M., & Kulikowski, C. A. (1991). Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems. Morgan Kaufmann Publishers Inc. Witten, I. H., Frank, E., & Hall, M. a. (2011). Data Mining: Practical Machine Learning Tools and Techniques. In Complementary literature None. 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spelling	De-La-Hoz-Franco, EmiroDiaz Martínez, JorgePatiño Saucedo, Janns Álvaro2021-05-12T18:22:03Z2021-05-12T18:22:03Z2019https://hdl.handle.net/11323/8249Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Ambient assisted living (AAL), focus on generating innovative products and services in order to aid and medical attention to elderly people who suffer from neurodegenerative diseases or a disability. This research area is responsible for the development of activity recognition systems (ARS) which are based on Human Activity Recognition (HAR), specifically in activities of daily life (ADL) in indoor environments. These systems make it possible to identify the type of activity that people carry out, offering a possibility of effective assistance that allows them to carry out daily activities with total normality. The performance of the ARS in the HAR process must be evaluated through the approach of experimental scenarios with data sets available by the scientific community in online repositories, this work proposes a variety of combinations of machine learning algorithms with feature selection algorithms, obtaining as a result a functional model for the HAR, which combines the classification algorithm Logistic model trees (LMT) and the feature selection algorithm One R.Los ambientes asistidos para la vida - AAL por sus siglas en inglés (Ambient Assisted Living), se enfocan en generar productos y servicios innovadores en aras de proporcionar asistencia y atención médica a personas de avanzada edad que padezcan enfermedades neurodegenerativas o alguna discapacidad. Esta área de investigación se encarga del desarrollo de sistemas para el reconocimiento de actividad - ARS (Activity Recognition Systems) los cuales están basados en el reconocimiento de actividades humanas - HAR (Human Activity Recognition), específicamente en actividades de la vida diaria - ADL (Activities of Daily Living) en ambientes interiores (indoor). Estos sistemas permiten identificar el tipo de actividad que realizan las personas, ofreciendo una posibilidad de asistencia efectiva que les permita llevar a cabo actividades cotidianas con total normalidad. El desempeño de los ARS en el proceso de HAR, debe ser evaluado a través del planteamiento de escenarios experimentales con conjuntos de datos dispuestos por la comunidad científica en repositorios en linea, este trabajo plantea una variedad de combinaciones de técnicas de machine learning con técnicas de selección de características, obteniendo como resultado un modelo funcional para el HAR, que combina la técnica de clasificación árboles para el modelamiento logístico - LMT por sus siglas en inglés (Logistic Model Trees) y la técnica de selección de características One R.Patiño Saucedo, Janns Álvaroapplication/pdfspaCorporación Universidad de la CostaMaestría en Ingeniería con Énfasis en SistemasAttribution-NonCommercial-ShareAlike 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Human Activity Recognition (HAR)Machine learningClassificationFeature selectionReconocimiento de Actividades Humanas (HAR)Aprendizaje automáticoClasificaciónSelección de característicasModelo predictivo para el reconocimiento de actividades humanas basado en técnicas de Machine Learning y de selección de característicasTrabajo de grado - MaestríaTextinfo:eu-repo/semantics/masterThesishttp://purl.org/redcol/resource_type/TMinfo:eu-repo/semantics/acceptedVersionAggarwal, J. 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Applied Artificial Intelligence, 17(5–6), 375–381. https://doi.org/10.1080/713827180PublicationCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-81031https://repositorio.cuc.edu.co/bitstreams/6280126f-aef8-4ca7-9d98-48d6fda8ed34/download934f4ca17e109e0a05eaeaba504d7ce4MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-83196https://repositorio.cuc.edu.co/bitstreams/3f28dddf-9714-41da-8f4f-c701883bee19/downloade30e9215131d99561d40d6b0abbe9badMD53ORIGINALMODELO PREDICTIVO PARA EL RECONOCIMIENTO DE ACTIVIDADES HUMANAS BASADO EN TÉCNICAS DE MACHINE LEARNING Y DE SELECCIÓN DE CARACTERÍSTICAS.pdfMODELO PREDICTIVO PARA EL RECONOCIMIENTO DE ACTIVIDADES HUMANAS BASADO EN TÉCNICAS DE MACHINE LEARNING Y DE SELECCIÓN DE CARACTERÍSTICAS.pdfapplication/pdf1728674https://repositorio.cuc.edu.co/bitstreams/fb911261-c983-4422-bd31-b2c5c8f77a28/download48e3c0c607da980b94f09dbdc02bd5e6MD51THUMBNAILMODELO PREDICTIVO PARA EL RECONOCIMIENTO DE ACTIVIDADES HUMANAS BASADO EN TÉCNICAS DE 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Modelo predictivo para el reconocimiento de actividades humanas basado en técnicas de Machine Learning y de selección de características

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