{"id":1523,"date":"2022-12-20T12:49:54","date_gmt":"2022-12-20T12:49:54","guid":{"rendered":"https:\/\/sbia.org.br\/lnlm\/?page_id=1523"},"modified":"2022-12-20T12:50:07","modified_gmt":"2022-12-20T12:50:07","slug":"vol20-no2-art4","status":"publish","type":"page","link":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art4\/","title":{"rendered":"Application of Machine Learning Tools in the Evaluation of the Risk of Falls in the Elderly: An Integrative Review"},"content":{"rendered":"<p>Daniele A. Silva <a href=\"https:\/\/orcid.org\/0000-0001-8259-8656\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Nayra F. L. C. Branco <a href=\"https:\/\/orcid.org\/0000-0002-2569-7647\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Hermes Manoel G. C. Branco <a href=\"https:\/\/orcid.org\/0000-0003-4921-7035\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>&#038; Guilherme A. Barreto <a href=\"https:\/\/orcid.org\/0000-0002-7002-1216\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a><\/p>\n<p><strong>Abstract:<\/strong> This integrative review seeks to present an overview of the application of machine learning (ML) tools in the assessment of the risk of falls in the elderly. We searched the CAPES and IEEE Xplore Periodical databases, articles published in English, Portuguese and Spanish, in the last eleven years. Thirteen articles were selected. Most studies use data from sensors to classify the risk of falling and compare the results obtained with results of clinical tests or history of falls. Some studies carried out the selection of characteristics of the collected signals. Research that compared CI tools and conventional scales pointed to a certain superiority of the former. In the selected articles, Multilayer Perceptron (MLP) neural networks were the most explored. It was possible to observe that the ML tools can be applied in the assessment of the risk of falls in the elderly as a classification resource, showing good results.<\/p>\n<p><strong>Keywords:<\/strong> Machine learning, elderly assistance, fall accidents, geriatric assessment.<\/p>\n<p><strong>DOI code:<\/strong> <a href=\"http:\/\/dx.doi.org\/10.21528\/lnlm-vol20-no2-art4\">10.21528\/lnlm-vol20-no2-art4<\/a><\/p>\n<p><strong>PDF file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2022\/12\/vol20-no2-art4.pdf\">vol20-no2-art4.pdf<\/a><\/p>\n<p><strong>BibTex file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2022\/12\/vol20-no2-art4.bib\">vol20-no2-art4.bib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Daniele A. Silva , Nayra F. L. C. Branco , Hermes Manoel G. C. Branco &#038; Guilherme A. Barreto Abstract: This integrative review seeks to present an overview of the application of machine learning (ML) tools in the assessment of <a href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art4\/\" class=\"read-more\">Read More &#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":1512,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1523","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Application of Machine Learning Tools in the Evaluation of the Risk of Falls in the Elderly: An Integrative Review - Learning and NonLinear Models<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art4\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Application of Machine Learning Tools in the Evaluation of the Risk of Falls in the Elderly: An Integrative Review - Learning and NonLinear Models\" \/>\n<meta property=\"og:description\" content=\"Daniele A. Silva , Nayra F. L. C. Branco , Hermes Manoel G. C. Branco &#038; Guilherme A. Barreto Abstract: This integrative review seeks to present an overview of the application of machine learning (ML) tools in the assessment of Read More ...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art4\/\" \/>\n<meta property=\"og:site_name\" content=\"Learning and NonLinear Models\" \/>\n<meta property=\"article:modified_time\" content=\"2022-12-20T12:50:07+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. tempo de leitura\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minuto\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art4\/\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art4\/\",\"name\":\"Application of Machine Learning Tools in the Evaluation of the Risk of Falls in the Elderly: An Integrative Review - Learning and NonLinear Models\",\"isPartOf\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art4\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art4\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\",\"datePublished\":\"2022-12-20T12:49:54+00:00\",\"dateModified\":\"2022-12-20T12:50:07+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art4\/#breadcrumb\"},\"inLanguage\":\"pt-BR\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art4\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"pt-BR\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art4\/#primaryimage\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\",\"contentUrl\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art4\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Browse issues\",\"item\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Learning &#038; Nonlinear Models &#8211; L&#038;NLM &#8211; Volume 20 &#8211; N\u00famero 2\",\"item\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Application of Machine Learning Tools in the Evaluation of the Risk of Falls in the Elderly: An Integrative Review\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#website\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/\",\"name\":\"Learning and NonLinear Models\",\"description\":\"\",\"publisher\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/sbia.org.br\/lnlm\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"pt-BR\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#organization\",\"name\":\"Learning and NonLinear Models\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"pt-BR\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/07\/logo-lnlm.png\",\"contentUrl\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/07\/logo-lnlm.png\",\"width\":398,\"height\":94,\"caption\":\"Learning and NonLinear Models\"},\"image\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#\/schema\/logo\/image\/\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Application of Machine Learning Tools in the Evaluation of the Risk of Falls in the Elderly: An Integrative Review - Learning and NonLinear Models","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol20-no2\/vol20-no2-art4\/","og_locale":"pt_BR","og_type":"article","og_title":"Application of Machine Learning Tools in the Evaluation of the Risk of Falls in the Elderly: An Integrative Review - Learning and NonLinear Models","og_description":"Daniele A. 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