Review of intelligent sensor-based systems for pressure ulcer prevention.

Detalhes bibliográficos
Autor(a) principal: Silva, Arlindo
Data de Publicação: 2021
Outros Autores: Metrôlho, José Carlos, Ribeiro, Fernando Reinaldo, Fidalgo, Filipe, Santos, Osvaldo, Dionísio, Rogério Pais
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.11/7908
Resumo: Pressure ulcers are a critical issue not only for patients, decreasing their quality of life, but also for healthcare professionals, contributing to burnout from continuous monitoring, with a consequent increase in healthcare costs. Due to the relevance of this problem, many hardware and software approaches have been proposed to ameliorate some aspects of pressure ulcer prevention and monitoring. In this article, we focus on reviewing solutions that use sensor-based data, possibly in combination with other intrinsic or extrinsic information, processed by some form of intelligent algorithm, to provide healthcare professionals with knowledge that improves the decision-making process when dealing with a patient at risk of developing pressure ulcers. We used a systematic approach to select 21 studies that were thoroughly reviewed and summarized, considering which sensors and algorithms were used, the most relevant data features, the recommendations provided, and the results obtained after deployment. This review allowed us not only to describe the state of the art regarding the previous items, but also to identify the three main stages where intelligent algorithms can bring meaningful improvement to pressure ulcer prevention and mitigation. Finally, as a result of this review and following discussion, we drew guidelines for a general architecture of an intelligent pressure ulcer prevention system.
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spelling Review of intelligent sensor-based systems for pressure ulcer prevention.artificial intelligence; sensor-based systems; literature review; machine learning; pressure injury prevention; pressure ulcers preventionPressure ulcers are a critical issue not only for patients, decreasing their quality of life, but also for healthcare professionals, contributing to burnout from continuous monitoring, with a consequent increase in healthcare costs. Due to the relevance of this problem, many hardware and software approaches have been proposed to ameliorate some aspects of pressure ulcer prevention and monitoring. In this article, we focus on reviewing solutions that use sensor-based data, possibly in combination with other intrinsic or extrinsic information, processed by some form of intelligent algorithm, to provide healthcare professionals with knowledge that improves the decision-making process when dealing with a patient at risk of developing pressure ulcers. We used a systematic approach to select 21 studies that were thoroughly reviewed and summarized, considering which sensors and algorithms were used, the most relevant data features, the recommendations provided, and the results obtained after deployment. This review allowed us not only to describe the state of the art regarding the previous items, but also to identify the three main stages where intelligent algorithms can bring meaningful improvement to pressure ulcer prevention and mitigation. Finally, as a result of this review and following discussion, we drew guidelines for a general architecture of an intelligent pressure ulcer prevention system.MDPIRepositório Científico do Instituto Politécnico de Castelo BrancoSilva, ArlindoMetrôlho, José CarlosRibeiro, Fernando ReinaldoFidalgo, FilipeSantos, OsvaldoDionísio, Rogério Pais2022-02-23T10:35:26Z20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.11/7908engSILVA, A. [et al.] (2022) - Review of intelligent sensor-based systems for pressure ulcer prevention. Computers. DOI https://doi.org/10.3390/computers1101000610.3390/computers11010006info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-25T01:47:42Zoai:repositorio.ipcb.pt:10400.11/7908Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:38:22.957148Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Review of intelligent sensor-based systems for pressure ulcer prevention.
title Review of intelligent sensor-based systems for pressure ulcer prevention.
spellingShingle Review of intelligent sensor-based systems for pressure ulcer prevention.
Silva, Arlindo
artificial intelligence; sensor-based systems; literature review; machine learning; pressure injury prevention; pressure ulcers prevention
title_short Review of intelligent sensor-based systems for pressure ulcer prevention.
title_full Review of intelligent sensor-based systems for pressure ulcer prevention.
title_fullStr Review of intelligent sensor-based systems for pressure ulcer prevention.
title_full_unstemmed Review of intelligent sensor-based systems for pressure ulcer prevention.
title_sort Review of intelligent sensor-based systems for pressure ulcer prevention.
author Silva, Arlindo
author_facet Silva, Arlindo
Metrôlho, José Carlos
Ribeiro, Fernando Reinaldo
Fidalgo, Filipe
Santos, Osvaldo
Dionísio, Rogério Pais
author_role author
author2 Metrôlho, José Carlos
Ribeiro, Fernando Reinaldo
Fidalgo, Filipe
Santos, Osvaldo
Dionísio, Rogério Pais
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico de Castelo Branco
dc.contributor.author.fl_str_mv Silva, Arlindo
Metrôlho, José Carlos
Ribeiro, Fernando Reinaldo
Fidalgo, Filipe
Santos, Osvaldo
Dionísio, Rogério Pais
dc.subject.por.fl_str_mv artificial intelligence; sensor-based systems; literature review; machine learning; pressure injury prevention; pressure ulcers prevention
topic artificial intelligence; sensor-based systems; literature review; machine learning; pressure injury prevention; pressure ulcers prevention
description Pressure ulcers are a critical issue not only for patients, decreasing their quality of life, but also for healthcare professionals, contributing to burnout from continuous monitoring, with a consequent increase in healthcare costs. Due to the relevance of this problem, many hardware and software approaches have been proposed to ameliorate some aspects of pressure ulcer prevention and monitoring. In this article, we focus on reviewing solutions that use sensor-based data, possibly in combination with other intrinsic or extrinsic information, processed by some form of intelligent algorithm, to provide healthcare professionals with knowledge that improves the decision-making process when dealing with a patient at risk of developing pressure ulcers. We used a systematic approach to select 21 studies that were thoroughly reviewed and summarized, considering which sensors and algorithms were used, the most relevant data features, the recommendations provided, and the results obtained after deployment. This review allowed us not only to describe the state of the art regarding the previous items, but also to identify the three main stages where intelligent algorithms can bring meaningful improvement to pressure ulcer prevention and mitigation. Finally, as a result of this review and following discussion, we drew guidelines for a general architecture of an intelligent pressure ulcer prevention system.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-01-01T00:00:00Z
2022-02-23T10:35:26Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.11/7908
url http://hdl.handle.net/10400.11/7908
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv SILVA, A. [et al.] (2022) - Review of intelligent sensor-based systems for pressure ulcer prevention. Computers. DOI https://doi.org/10.3390/computers11010006
10.3390/computers11010006
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