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Contactless Gait Assessment in Home-like Environments
Gait analysis is an important part of assessments for a variety of health conditions, specifically neurodegenerative diseases. Currently, most methods for gait assessment are based on manual scoring of certain tasks or restrictive technologies. We present an unobtrusive sensor system based on light...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473097/ https://www.ncbi.nlm.nih.gov/pubmed/34577412 http://dx.doi.org/10.3390/s21186205 |
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author | Botros, Angela Gyger, Nathan Schütz, Narayan Single, Michael Nef, Tobias Gerber, Stephan M. |
author_facet | Botros, Angela Gyger, Nathan Schütz, Narayan Single, Michael Nef, Tobias Gerber, Stephan M. |
author_sort | Botros, Angela |
collection | PubMed |
description | Gait analysis is an important part of assessments for a variety of health conditions, specifically neurodegenerative diseases. Currently, most methods for gait assessment are based on manual scoring of certain tasks or restrictive technologies. We present an unobtrusive sensor system based on light detection and ranging sensor technology for use in home-like environments. In our evaluation, we compared six different gait parameters, based on recordings from 25 different people performing eight different walks each, resulting in 200 unique measurements. We compared the proposed sensor system against two state-of-the art technologies, a pressure mat and a set of inertial measurement unit sensors. In addition to test usability and long-term measurement, multi-hour recordings were conducted. Our evaluation showed very high correlation ([Formula: see text]) with the gold standards across all assessed gait parameters except for cycle time ([Formula: see text]). Similarly, the coefficient of determination was high ([Formula: see text]) for all gait parameters except cycle time. The highest correlation was achieved for stride length and velocity ([Formula: see text]). Furthermore, the multi-hour recordings did not show the systematic drift of measurements over time. Overall, the unobtrusive gait measurement system allows for contactless, highly accurate long- and short-term assessments of gait in home-like environments. |
format | Online Article Text |
id | pubmed-8473097 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-84730972021-09-28 Contactless Gait Assessment in Home-like Environments Botros, Angela Gyger, Nathan Schütz, Narayan Single, Michael Nef, Tobias Gerber, Stephan M. Sensors (Basel) Article Gait analysis is an important part of assessments for a variety of health conditions, specifically neurodegenerative diseases. Currently, most methods for gait assessment are based on manual scoring of certain tasks or restrictive technologies. We present an unobtrusive sensor system based on light detection and ranging sensor technology for use in home-like environments. In our evaluation, we compared six different gait parameters, based on recordings from 25 different people performing eight different walks each, resulting in 200 unique measurements. We compared the proposed sensor system against two state-of-the art technologies, a pressure mat and a set of inertial measurement unit sensors. In addition to test usability and long-term measurement, multi-hour recordings were conducted. Our evaluation showed very high correlation ([Formula: see text]) with the gold standards across all assessed gait parameters except for cycle time ([Formula: see text]). Similarly, the coefficient of determination was high ([Formula: see text]) for all gait parameters except cycle time. The highest correlation was achieved for stride length and velocity ([Formula: see text]). Furthermore, the multi-hour recordings did not show the systematic drift of measurements over time. Overall, the unobtrusive gait measurement system allows for contactless, highly accurate long- and short-term assessments of gait in home-like environments. MDPI 2021-09-16 /pmc/articles/PMC8473097/ /pubmed/34577412 http://dx.doi.org/10.3390/s21186205 Text en © 2021 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 | Article Botros, Angela Gyger, Nathan Schütz, Narayan Single, Michael Nef, Tobias Gerber, Stephan M. Contactless Gait Assessment in Home-like Environments |
title | Contactless Gait Assessment in Home-like Environments |
title_full | Contactless Gait Assessment in Home-like Environments |
title_fullStr | Contactless Gait Assessment in Home-like Environments |
title_full_unstemmed | Contactless Gait Assessment in Home-like Environments |
title_short | Contactless Gait Assessment in Home-like Environments |
title_sort | contactless gait assessment in home-like environments |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473097/ https://www.ncbi.nlm.nih.gov/pubmed/34577412 http://dx.doi.org/10.3390/s21186205 |
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