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On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator
Gait analysis can provide valuable information on a person’s condition and rehabilitation progress. Gait is typically captured using external equipment and/or wearable sensors. These tests are largely constrained to specific controlled environments. In addition, gait analysis often requires experts...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5134555/ https://www.ncbi.nlm.nih.gov/pubmed/27834911 http://dx.doi.org/10.3390/s16111896 |
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author | Ballesteros, Joaquin Urdiales, Cristina Martinez, Antonio B. van Dieën, Jaap H. |
author_facet | Ballesteros, Joaquin Urdiales, Cristina Martinez, Antonio B. van Dieën, Jaap H. |
author_sort | Ballesteros, Joaquin |
collection | PubMed |
description | Gait analysis can provide valuable information on a person’s condition and rehabilitation progress. Gait is typically captured using external equipment and/or wearable sensors. These tests are largely constrained to specific controlled environments. In addition, gait analysis often requires experts for calibration, operation and/or to place sensors on volunteers. Alternatively, mobility support devices like rollators can be equipped with onboard sensors to monitor gait parameters, while users perform their Activities of Daily Living. Gait analysis in rollators may use odometry and force sensors in the handlebars. However, force based estimation of gait parameters is less accurate than traditional methods, especially when rollators are not properly used. This paper presents an evaluation of force based gait analysis using a smart rollator on different groups of users to determine when this methodology is applicable. In a second stage, the rollator is used in combination with two lab-based gait analysis systems to assess the rollator estimation error. Our results show that: (i) there is an inverse relation between the variance in the force difference between handlebars and support on the handlebars—related to the user condition—and the estimation error; and (ii) this error is lower than 10% when the variation in the force difference is above 7 N. This lower limit was exceeded by the 95.83% of our challenged volunteers. In conclusion, rollators are useful for gait characterization as long as users really need the device for ambulation. |
format | Online Article Text |
id | pubmed-5134555 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-51345552017-01-03 On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator Ballesteros, Joaquin Urdiales, Cristina Martinez, Antonio B. van Dieën, Jaap H. Sensors (Basel) Article Gait analysis can provide valuable information on a person’s condition and rehabilitation progress. Gait is typically captured using external equipment and/or wearable sensors. These tests are largely constrained to specific controlled environments. In addition, gait analysis often requires experts for calibration, operation and/or to place sensors on volunteers. Alternatively, mobility support devices like rollators can be equipped with onboard sensors to monitor gait parameters, while users perform their Activities of Daily Living. Gait analysis in rollators may use odometry and force sensors in the handlebars. However, force based estimation of gait parameters is less accurate than traditional methods, especially when rollators are not properly used. This paper presents an evaluation of force based gait analysis using a smart rollator on different groups of users to determine when this methodology is applicable. In a second stage, the rollator is used in combination with two lab-based gait analysis systems to assess the rollator estimation error. Our results show that: (i) there is an inverse relation between the variance in the force difference between handlebars and support on the handlebars—related to the user condition—and the estimation error; and (ii) this error is lower than 10% when the variation in the force difference is above 7 N. This lower limit was exceeded by the 95.83% of our challenged volunteers. In conclusion, rollators are useful for gait characterization as long as users really need the device for ambulation. MDPI 2016-11-10 /pmc/articles/PMC5134555/ /pubmed/27834911 http://dx.doi.org/10.3390/s16111896 Text en © 2016 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 (CC-BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ballesteros, Joaquin Urdiales, Cristina Martinez, Antonio B. van Dieën, Jaap H. On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator |
title | On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator |
title_full | On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator |
title_fullStr | On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator |
title_full_unstemmed | On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator |
title_short | On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator |
title_sort | on gait analysis estimation errors using force sensors on a smart rollator |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5134555/ https://www.ncbi.nlm.nih.gov/pubmed/27834911 http://dx.doi.org/10.3390/s16111896 |
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