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Fall Risk Assessment Using Wearable Sensors: A Narrative Review
Recently, fall risk assessment has been a main focus in fall-related research. Wearable sensors have been used to increase the objectivity of this assessment, building on the traditional use of oversimplified questionnaires. However, it is necessary to define standard procedures that will us enable...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838304/ https://www.ncbi.nlm.nih.gov/pubmed/35161731 http://dx.doi.org/10.3390/s22030984 |
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author | Ferreira, Rafael N. Ribeiro, Nuno Ferrete Santos, Cristina P. |
author_facet | Ferreira, Rafael N. Ribeiro, Nuno Ferrete Santos, Cristina P. |
author_sort | Ferreira, Rafael N. |
collection | PubMed |
description | Recently, fall risk assessment has been a main focus in fall-related research. Wearable sensors have been used to increase the objectivity of this assessment, building on the traditional use of oversimplified questionnaires. However, it is necessary to define standard procedures that will us enable to acknowledge the multifactorial causes behind fall events while tackling the heterogeneity of the currently developed systems. Thus, it is necessary to identify the different specifications and demands of each fall risk assessment method. Hence, this manuscript provides a narrative review on the fall risk assessment methods performed in the scientific literature using wearable sensors. For each identified method, a comprehensive analysis has been carried out in order to find trends regarding the most used sensors and its characteristics, activities performed in the experimental protocol, and algorithms used to classify the fall risk. We also verified how studies performed the validation process of the developed fall risk assessment systems. The identification of trends for each fall risk assessment method would help researchers in the design of standard innovative solutions and enhance the reliability of this assessment towards a homogeneous benchmark solution. |
format | Online Article Text |
id | pubmed-8838304 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88383042022-02-13 Fall Risk Assessment Using Wearable Sensors: A Narrative Review Ferreira, Rafael N. Ribeiro, Nuno Ferrete Santos, Cristina P. Sensors (Basel) Review Recently, fall risk assessment has been a main focus in fall-related research. Wearable sensors have been used to increase the objectivity of this assessment, building on the traditional use of oversimplified questionnaires. However, it is necessary to define standard procedures that will us enable to acknowledge the multifactorial causes behind fall events while tackling the heterogeneity of the currently developed systems. Thus, it is necessary to identify the different specifications and demands of each fall risk assessment method. Hence, this manuscript provides a narrative review on the fall risk assessment methods performed in the scientific literature using wearable sensors. For each identified method, a comprehensive analysis has been carried out in order to find trends regarding the most used sensors and its characteristics, activities performed in the experimental protocol, and algorithms used to classify the fall risk. We also verified how studies performed the validation process of the developed fall risk assessment systems. The identification of trends for each fall risk assessment method would help researchers in the design of standard innovative solutions and enhance the reliability of this assessment towards a homogeneous benchmark solution. MDPI 2022-01-27 /pmc/articles/PMC8838304/ /pubmed/35161731 http://dx.doi.org/10.3390/s22030984 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Ferreira, Rafael N. Ribeiro, Nuno Ferrete Santos, Cristina P. Fall Risk Assessment Using Wearable Sensors: A Narrative Review |
title | Fall Risk Assessment Using Wearable Sensors: A Narrative Review |
title_full | Fall Risk Assessment Using Wearable Sensors: A Narrative Review |
title_fullStr | Fall Risk Assessment Using Wearable Sensors: A Narrative Review |
title_full_unstemmed | Fall Risk Assessment Using Wearable Sensors: A Narrative Review |
title_short | Fall Risk Assessment Using Wearable Sensors: A Narrative Review |
title_sort | fall risk assessment using wearable sensors: a narrative review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838304/ https://www.ncbi.nlm.nih.gov/pubmed/35161731 http://dx.doi.org/10.3390/s22030984 |
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