Physiological and behavior monitoring systems for smart healthcare environments: a review

Detalhes bibliográficos
Autor(a) principal: Jacob Rodrigues, M.
Data de Publicação: 2020
Outros Autores: Postolache, O., Cercas, F.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/20429
Resumo: Healthcare optimization has become increasingly important in the current era, where numerous challenges are posed by population ageing phenomena and the demand for higher quality of the healthcare services. The implementation of Internet of Things (IoT) in the healthcare ecosystem has been one of the best solutions to address these challenges and therefore to prevent and diagnose possible health impairments in people. The remote monitoring of environmental parameters and how they can cause or mediate any disease, and the monitoring of human daily activities and physiological parameters are among the vast applications of IoT in healthcare, which has brought extensive attention of academia and industry. Assisted and smart tailored environments are possible with the implementation of such technologies that bring personal healthcare to any individual, while living in their preferred environments. In this paper we address several requirements for the development of such environments, namely the deployment of physiological signs monitoring systems, daily activity recognition techniques, as well as indoor air quality monitoring solutions. The machine learning methods that are most used in the literature for activity recognition and body motion analysis are also referred. Furthermore, the importance of physical and cognitive training of the elderly population through the implementation of exergames and immersive environments is also addressed
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spelling Physiological and behavior monitoring systems for smart healthcare environments: a reviewHealthcareInternet of thingsSmart environmentsPhysiological signs monitoringActivity recognitionIndoor air qualityHealthcare optimization has become increasingly important in the current era, where numerous challenges are posed by population ageing phenomena and the demand for higher quality of the healthcare services. The implementation of Internet of Things (IoT) in the healthcare ecosystem has been one of the best solutions to address these challenges and therefore to prevent and diagnose possible health impairments in people. The remote monitoring of environmental parameters and how they can cause or mediate any disease, and the monitoring of human daily activities and physiological parameters are among the vast applications of IoT in healthcare, which has brought extensive attention of academia and industry. Assisted and smart tailored environments are possible with the implementation of such technologies that bring personal healthcare to any individual, while living in their preferred environments. In this paper we address several requirements for the development of such environments, namely the deployment of physiological signs monitoring systems, daily activity recognition techniques, as well as indoor air quality monitoring solutions. The machine learning methods that are most used in the literature for activity recognition and body motion analysis are also referred. Furthermore, the importance of physical and cognitive training of the elderly population through the implementation of exergames and immersive environments is also addressedMultidisciplinary Digital Publishing Institute2020-04-27T14:33:10Z2020-01-01T00:00:00Z20202020-04-27T15:32:09Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/pdfhttp://hdl.handle.net/10071/20429eng1424-822010.3390/s20082186Jacob Rodrigues, M.Postolache, O.Cercas, F.info: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:RCAAP2023-11-09T17:26:45Zoai:repositorio.iscte-iul.pt:10071/20429Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:11:57.828386Repositório 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 Physiological and behavior monitoring systems for smart healthcare environments: a review
title Physiological and behavior monitoring systems for smart healthcare environments: a review
spellingShingle Physiological and behavior monitoring systems for smart healthcare environments: a review
Jacob Rodrigues, M.
Healthcare
Internet of things
Smart environments
Physiological signs monitoring
Activity recognition
Indoor air quality
title_short Physiological and behavior monitoring systems for smart healthcare environments: a review
title_full Physiological and behavior monitoring systems for smart healthcare environments: a review
title_fullStr Physiological and behavior monitoring systems for smart healthcare environments: a review
title_full_unstemmed Physiological and behavior monitoring systems for smart healthcare environments: a review
title_sort Physiological and behavior monitoring systems for smart healthcare environments: a review
author Jacob Rodrigues, M.
author_facet Jacob Rodrigues, M.
Postolache, O.
Cercas, F.
author_role author
author2 Postolache, O.
Cercas, F.
author2_role author
author
dc.contributor.author.fl_str_mv Jacob Rodrigues, M.
Postolache, O.
Cercas, F.
dc.subject.por.fl_str_mv Healthcare
Internet of things
Smart environments
Physiological signs monitoring
Activity recognition
Indoor air quality
topic Healthcare
Internet of things
Smart environments
Physiological signs monitoring
Activity recognition
Indoor air quality
description Healthcare optimization has become increasingly important in the current era, where numerous challenges are posed by population ageing phenomena and the demand for higher quality of the healthcare services. The implementation of Internet of Things (IoT) in the healthcare ecosystem has been one of the best solutions to address these challenges and therefore to prevent and diagnose possible health impairments in people. The remote monitoring of environmental parameters and how they can cause or mediate any disease, and the monitoring of human daily activities and physiological parameters are among the vast applications of IoT in healthcare, which has brought extensive attention of academia and industry. Assisted and smart tailored environments are possible with the implementation of such technologies that bring personal healthcare to any individual, while living in their preferred environments. In this paper we address several requirements for the development of such environments, namely the deployment of physiological signs monitoring systems, daily activity recognition techniques, as well as indoor air quality monitoring solutions. The machine learning methods that are most used in the literature for activity recognition and body motion analysis are also referred. Furthermore, the importance of physical and cognitive training of the elderly population through the implementation of exergames and immersive environments is also addressed
publishDate 2020
dc.date.none.fl_str_mv 2020-04-27T14:33:10Z
2020-01-01T00:00:00Z
2020
2020-04-27T15:32:09Z
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dc.relation.none.fl_str_mv 1424-8220
10.3390/s20082186
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dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
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