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Automatic Fall Monitoring: A Review
Falls and fall-related injuries are major incidents, especially for elderly people, which often mark the onset of major deterioration of health. More than one-third of home-dwelling people aged 65 or above and two-thirds of those in residential care fall once or more each year. Reliable fall detecti...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4166886/ https://www.ncbi.nlm.nih.gov/pubmed/25046016 http://dx.doi.org/10.3390/s140712900 |
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author | Pannurat, Natthapon Thiemjarus, Surapa Nantajeewarawat, Ekawit |
author_facet | Pannurat, Natthapon Thiemjarus, Surapa Nantajeewarawat, Ekawit |
author_sort | Pannurat, Natthapon |
collection | PubMed |
description | Falls and fall-related injuries are major incidents, especially for elderly people, which often mark the onset of major deterioration of health. More than one-third of home-dwelling people aged 65 or above and two-thirds of those in residential care fall once or more each year. Reliable fall detection, as well as prevention, is an important research topic for monitoring elderly living alone in residential or hospital units. The aim of this study is to review the existing fall detection systems and some of the key research challenges faced by the research community in this field. We categorize the existing platforms into two groups: wearable and ambient devices; the classification methods are divided into rule-based and machine learning techniques. The relative merit and potential drawbacks are discussed, and we also outline some of the outstanding research challenges that emerging new platforms need to address. |
format | Online Article Text |
id | pubmed-4166886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-41668862014-09-19 Automatic Fall Monitoring: A Review Pannurat, Natthapon Thiemjarus, Surapa Nantajeewarawat, Ekawit Sensors (Basel) Review Falls and fall-related injuries are major incidents, especially for elderly people, which often mark the onset of major deterioration of health. More than one-third of home-dwelling people aged 65 or above and two-thirds of those in residential care fall once or more each year. Reliable fall detection, as well as prevention, is an important research topic for monitoring elderly living alone in residential or hospital units. The aim of this study is to review the existing fall detection systems and some of the key research challenges faced by the research community in this field. We categorize the existing platforms into two groups: wearable and ambient devices; the classification methods are divided into rule-based and machine learning techniques. The relative merit and potential drawbacks are discussed, and we also outline some of the outstanding research challenges that emerging new platforms need to address. MDPI 2014-07-18 /pmc/articles/PMC4166886/ /pubmed/25046016 http://dx.doi.org/10.3390/s140712900 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Review Pannurat, Natthapon Thiemjarus, Surapa Nantajeewarawat, Ekawit Automatic Fall Monitoring: A Review |
title | Automatic Fall Monitoring: A Review |
title_full | Automatic Fall Monitoring: A Review |
title_fullStr | Automatic Fall Monitoring: A Review |
title_full_unstemmed | Automatic Fall Monitoring: A Review |
title_short | Automatic Fall Monitoring: A Review |
title_sort | automatic fall monitoring: a review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4166886/ https://www.ncbi.nlm.nih.gov/pubmed/25046016 http://dx.doi.org/10.3390/s140712900 |
work_keys_str_mv | AT pannuratnatthapon automaticfallmonitoringareview AT thiemjarussurapa automaticfallmonitoringareview AT nantajeewarawatekawit automaticfallmonitoringareview |