The state of knowledge on technologies and their use for fall detection: A scoping review

Background Globally, populations are aging with increasing life spans. The normal aging process and the resulting disabilities increase fall risks. Falls are an important cause of injury, loss of independence and institutionalization. Technologies have been developed to detect falls and reduce their...

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Autores:
Tipo de recurso:
Fecha de publicación:
2018
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/22133
Acceso en línea:
https://doi.org/10.1016/j.ijmedinf.2017.12.015
https://repository.urosario.edu.co/handle/10336/22133
Palabra clave:
Controlled environment
Current technology
Falls
Implementation cost
Literature reviews
Older adults
Scoping review
Technology readiness levels
Wearable sensors
Algorithm
Assistive technology
Data mining
Fuzzy logic
Hidden Markov model
Internet
Journal impact factor
Knowledge
Medical information
Medical technology
Priority journal
Qualitative research
Review
Support vector machine
Aged
Attitude to health
Falling
Human
Quality of life
Statistics and numerical data
Accidental Falls
Aged
Biomedical Technology
Humans
Quality of Life
Falls
Older adults
Scoping review
Technology
Attitudes
Practice
Health Knowledge
Rights
License
Abierto (Texto Completo)
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network_acronym_str EDOCUR2
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repository_id_str
spelling 109c5245-fbf8-46dd-a93a-4fbc1fcb7b54-1a129ce83-41fe-41ee-92c5-c3bbdca6ba58-1dc42dfaf-7fb2-4603-9516-001a56e2500b-16ee62dd2-7802-4f09-a893-353f76f6d3c3-1c27105a4-92d5-4105-aa19-8bbf8d49ad11-1935e83f4-8cd7-47b1-ad5e-da30ceae2d38-12020-05-25T23:55:35Z2020-05-25T23:55:35Z2018Background Globally, populations are aging with increasing life spans. The normal aging process and the resulting disabilities increase fall risks. Falls are an important cause of injury, loss of independence and institutionalization. Technologies have been developed to detect falls and reduce their consequences but their use and impact on quality of life remain debatable. Reviews on fall detection technologies exist but are not extensive. A comprehensive literature review on the state of knowledge of fall detection technologies can inform research, practice, and user adoption. Objectives To examine the extent and the diversity of current technologies for fall detection in older adults. Methods A scoping review design was used to search peer-reviewed literature on technologies to detect falls, published in English, French or Spanish since 2006. Data from the studies were analyzed descriptively. Results The literature search identified 3202 studies of which 118 were included for analysis. Ten types of technologies were identified ranging from wearable (e.g., inertial sensors) to ambient sensors (e.g., vision sensors). Their Technology Readiness Level was low (mean 4.54 SD 1.25; 95% CI [4.31, 4.77] out of a maximum of 9). Outcomes were typically evaluated on technological basis and in controlled environments. Few were evaluated in home settings or care units with older adults. Acceptability, implementation cost and barriers were seldom addressed. Conclusions Further research should focus on increasing Technology Readiness Levels of fall detection technologies by testing them in real-life settings with older adults. © 2017 Elsevier B.V.application/pdfhttps://doi.org/10.1016/j.ijmedinf.2017.12.01513865056https://repository.urosario.edu.co/handle/10336/22133engElsevier7158International Journal of Medical InformaticsVol. 111International Journal of Medical Informatics, ISSN:13865056, Vol.111,(2018); pp. 58-71https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039709375&doi=10.1016%2fj.ijmedinf.2017.12.015&partnerID=40&md5=13f22f15c072ab07155c63926502e49dAbierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURControlled environmentCurrent technologyFallsImplementation costLiterature reviewsOlder adultsScoping reviewTechnology readiness levelsWearable sensorsAlgorithmAssistive technologyData miningFuzzy logicHidden Markov modelInternetJournal impact factorKnowledgeMedical informationMedical technologyPriority journalQualitative researchReviewSupport vector machineAgedAttitude to healthFallingHumanQuality of lifeStatistics and numerical dataAccidental FallsAgedBiomedical TechnologyHumansQuality of LifeFallsOlder adultsScoping reviewTechnologyAttitudesPracticeHealth KnowledgeThe state of knowledge on technologies and their use for fall detection: A scoping reviewarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Lapierre N.Neubauer N.Miguel-Cruz A.Rios Rincon A.Liu L.Rousseau J.10336/22133oai:repository.urosario.edu.co:10336/221332022-05-02 07:37:20.255011https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv The state of knowledge on technologies and their use for fall detection: A scoping review
title The state of knowledge on technologies and their use for fall detection: A scoping review
spellingShingle The state of knowledge on technologies and their use for fall detection: A scoping review
Controlled environment
Current technology
Falls
Implementation cost
Literature reviews
Older adults
Scoping review
Technology readiness levels
Wearable sensors
Algorithm
Assistive technology
Data mining
Fuzzy logic
Hidden Markov model
Internet
Journal impact factor
Knowledge
Medical information
Medical technology
Priority journal
Qualitative research
Review
Support vector machine
Aged
Attitude to health
Falling
Human
Quality of life
Statistics and numerical data
Accidental Falls
Aged
Biomedical Technology
Humans
Quality of Life
Falls
Older adults
Scoping review
Technology
Attitudes
Practice
Health Knowledge
title_short The state of knowledge on technologies and their use for fall detection: A scoping review
title_full The state of knowledge on technologies and their use for fall detection: A scoping review
title_fullStr The state of knowledge on technologies and their use for fall detection: A scoping review
title_full_unstemmed The state of knowledge on technologies and their use for fall detection: A scoping review
title_sort The state of knowledge on technologies and their use for fall detection: A scoping review
dc.subject.keyword.spa.fl_str_mv Controlled environment
Current technology
Falls
Implementation cost
Literature reviews
Older adults
Scoping review
Technology readiness levels
Wearable sensors
Algorithm
Assistive technology
Data mining
Fuzzy logic
Hidden Markov model
Internet
Journal impact factor
Knowledge
Medical information
Medical technology
Priority journal
Qualitative research
Review
Support vector machine
Aged
Attitude to health
Falling
Human
Quality of life
Statistics and numerical data
Accidental Falls
Aged
Biomedical Technology
Humans
Quality of Life
Falls
Older adults
Scoping review
Technology
topic Controlled environment
Current technology
Falls
Implementation cost
Literature reviews
Older adults
Scoping review
Technology readiness levels
Wearable sensors
Algorithm
Assistive technology
Data mining
Fuzzy logic
Hidden Markov model
Internet
Journal impact factor
Knowledge
Medical information
Medical technology
Priority journal
Qualitative research
Review
Support vector machine
Aged
Attitude to health
Falling
Human
Quality of life
Statistics and numerical data
Accidental Falls
Aged
Biomedical Technology
Humans
Quality of Life
Falls
Older adults
Scoping review
Technology
Attitudes
Practice
Health Knowledge
dc.subject.keyword.eng.fl_str_mv Attitudes
Practice
Health Knowledge
description Background Globally, populations are aging with increasing life spans. The normal aging process and the resulting disabilities increase fall risks. Falls are an important cause of injury, loss of independence and institutionalization. Technologies have been developed to detect falls and reduce their consequences but their use and impact on quality of life remain debatable. Reviews on fall detection technologies exist but are not extensive. A comprehensive literature review on the state of knowledge of fall detection technologies can inform research, practice, and user adoption. Objectives To examine the extent and the diversity of current technologies for fall detection in older adults. Methods A scoping review design was used to search peer-reviewed literature on technologies to detect falls, published in English, French or Spanish since 2006. Data from the studies were analyzed descriptively. Results The literature search identified 3202 studies of which 118 were included for analysis. Ten types of technologies were identified ranging from wearable (e.g., inertial sensors) to ambient sensors (e.g., vision sensors). Their Technology Readiness Level was low (mean 4.54 SD 1.25; 95% CI [4.31, 4.77] out of a maximum of 9). Outcomes were typically evaluated on technological basis and in controlled environments. Few were evaluated in home settings or care units with older adults. Acceptability, implementation cost and barriers were seldom addressed. Conclusions Further research should focus on increasing Technology Readiness Levels of fall detection technologies by testing them in real-life settings with older adults. © 2017 Elsevier B.V.
publishDate 2018
dc.date.created.spa.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2020-05-25T23:55:35Z
dc.date.available.none.fl_str_mv 2020-05-25T23:55:35Z
dc.type.eng.fl_str_mv article
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.spa.spa.fl_str_mv Artículo
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1016/j.ijmedinf.2017.12.015
dc.identifier.issn.none.fl_str_mv 13865056
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/22133
url https://doi.org/10.1016/j.ijmedinf.2017.12.015
https://repository.urosario.edu.co/handle/10336/22133
identifier_str_mv 13865056
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationEndPage.none.fl_str_mv 71
dc.relation.citationStartPage.none.fl_str_mv 58
dc.relation.citationTitle.none.fl_str_mv International Journal of Medical Informatics
dc.relation.citationVolume.none.fl_str_mv Vol. 111
dc.relation.ispartof.spa.fl_str_mv International Journal of Medical Informatics, ISSN:13865056, Vol.111,(2018); pp. 58-71
dc.relation.uri.spa.fl_str_mv https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039709375&doi=10.1016%2fj.ijmedinf.2017.12.015&partnerID=40&md5=13f22f15c072ab07155c63926502e49d
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.spa.fl_str_mv Abierto (Texto Completo)
rights_invalid_str_mv Abierto (Texto Completo)
http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Elsevier
institution Universidad del Rosario
dc.source.instname.spa.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.spa.fl_str_mv reponame:Repositorio Institucional EdocUR
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
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