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Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor
Falls are one of the main concerns in the elderly population due to their high prevalence and associated consequences. Guidelines for the management of the elder with falls are comprised of multidimensional assessments, especially gait and balance. Daily clinical practice needs for timely, effortles...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244449/ https://www.ncbi.nlm.nih.gov/pubmed/37280388 http://dx.doi.org/10.1038/s41598-023-36241-x |
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author | Álvarez, Marta Neira Ruiz, Antonio R. Jiménez Neira, Guillermo García-Villamil Huertas-Hoyas, Elisabet Cerda, Maria Teresa Espinoza Delgado, Laura Pérez Robles, Elena Reina del-Ama, Antonio J. Ruiz-Ruiz, Luisa García-de-Villa, Sara Rodriguez-Sanchez, Cristina |
author_facet | Álvarez, Marta Neira Ruiz, Antonio R. Jiménez Neira, Guillermo García-Villamil Huertas-Hoyas, Elisabet Cerda, Maria Teresa Espinoza Delgado, Laura Pérez Robles, Elena Reina del-Ama, Antonio J. Ruiz-Ruiz, Luisa García-de-Villa, Sara Rodriguez-Sanchez, Cristina |
author_sort | Álvarez, Marta Neira |
collection | PubMed |
description | Falls are one of the main concerns in the elderly population due to their high prevalence and associated consequences. Guidelines for the management of the elder with falls are comprised of multidimensional assessments, especially gait and balance. Daily clinical practice needs for timely, effortless, and precise tools to assess gait. This work presents the clinical validation of the G-STRIDE system, a 6-axis inertial measurement unit (IMU) with onboard processing algorithms, that allows the calculation of walking-related metrics correlated with clinical markers of fall risk. A cross-sectional case-control study was conducted with 163 participants (falls and non-falls groups). All volunteers were assessed with clinical scales and conducted a 15-min walking test at a self-selected pace while wearing the G-STRIDE. G-STRIDE is a low-cost solution to facilitate the transfer to society and clinical evaluations. It is open hardware and flexible and, thus, has the advantage of providing runtime data processing. Walking descriptors were derived from the device, and a correlation analysis was conducted between walking and clinical variables. G-STRIDE allowed measuring walking parameters in non-restricted walking conditions (e.g. hallway). Walking parameters statistically discriminate between falls and non-falls groups. We found good/excellent estimation accuracy (ICC = 0.885; [Formula: see text] ) for walking speed, showing good/excellent correlation between gait speed and several clinical variables. G-STRIDE can calculate walking-related metrics that allow for discrimination between falls and non-falls groups, which correlates with clinical indicators of fall risk. A preliminary fall-risk assessment based on the walking parameters was found to improve the Timed Up and Go test in the identification of fallers. |
format | Online Article Text |
id | pubmed-10244449 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102444492023-06-08 Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor Álvarez, Marta Neira Ruiz, Antonio R. Jiménez Neira, Guillermo García-Villamil Huertas-Hoyas, Elisabet Cerda, Maria Teresa Espinoza Delgado, Laura Pérez Robles, Elena Reina del-Ama, Antonio J. Ruiz-Ruiz, Luisa García-de-Villa, Sara Rodriguez-Sanchez, Cristina Sci Rep Article Falls are one of the main concerns in the elderly population due to their high prevalence and associated consequences. Guidelines for the management of the elder with falls are comprised of multidimensional assessments, especially gait and balance. Daily clinical practice needs for timely, effortless, and precise tools to assess gait. This work presents the clinical validation of the G-STRIDE system, a 6-axis inertial measurement unit (IMU) with onboard processing algorithms, that allows the calculation of walking-related metrics correlated with clinical markers of fall risk. A cross-sectional case-control study was conducted with 163 participants (falls and non-falls groups). All volunteers were assessed with clinical scales and conducted a 15-min walking test at a self-selected pace while wearing the G-STRIDE. G-STRIDE is a low-cost solution to facilitate the transfer to society and clinical evaluations. It is open hardware and flexible and, thus, has the advantage of providing runtime data processing. Walking descriptors were derived from the device, and a correlation analysis was conducted between walking and clinical variables. G-STRIDE allowed measuring walking parameters in non-restricted walking conditions (e.g. hallway). Walking parameters statistically discriminate between falls and non-falls groups. We found good/excellent estimation accuracy (ICC = 0.885; [Formula: see text] ) for walking speed, showing good/excellent correlation between gait speed and several clinical variables. G-STRIDE can calculate walking-related metrics that allow for discrimination between falls and non-falls groups, which correlates with clinical indicators of fall risk. A preliminary fall-risk assessment based on the walking parameters was found to improve the Timed Up and Go test in the identification of fallers. Nature Publishing Group UK 2023-06-06 /pmc/articles/PMC10244449/ /pubmed/37280388 http://dx.doi.org/10.1038/s41598-023-36241-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Álvarez, Marta Neira Ruiz, Antonio R. Jiménez Neira, Guillermo García-Villamil Huertas-Hoyas, Elisabet Cerda, Maria Teresa Espinoza Delgado, Laura Pérez Robles, Elena Reina del-Ama, Antonio J. Ruiz-Ruiz, Luisa García-de-Villa, Sara Rodriguez-Sanchez, Cristina Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor |
title | Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor |
title_full | Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor |
title_fullStr | Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor |
title_full_unstemmed | Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor |
title_short | Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor |
title_sort | assessing falls in the elderly population using g-stride foot-mounted inertial sensor |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244449/ https://www.ncbi.nlm.nih.gov/pubmed/37280388 http://dx.doi.org/10.1038/s41598-023-36241-x |
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