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Wearable Inertial Measurement Units for Assessing Gait in Real-World Environments
BACKGROUND: Walking patterns can provide important indications of a person’s health status and be beneficial in the early diagnosis of individuals with a potential walking disorder. For appropriate gait analysis, it is critical that natural functional walking characteristics are captured, rather tha...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7044412/ https://www.ncbi.nlm.nih.gov/pubmed/32153420 http://dx.doi.org/10.3389/fphys.2020.00090 |
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author | Renggli, David Graf, Christina Tachatos, Nikolaos Singh, Navrag Meboldt, Mirko Taylor, William R. Stieglitz, Lennart Schmid Daners, Marianne |
author_facet | Renggli, David Graf, Christina Tachatos, Nikolaos Singh, Navrag Meboldt, Mirko Taylor, William R. Stieglitz, Lennart Schmid Daners, Marianne |
author_sort | Renggli, David |
collection | PubMed |
description | BACKGROUND: Walking patterns can provide important indications of a person’s health status and be beneficial in the early diagnosis of individuals with a potential walking disorder. For appropriate gait analysis, it is critical that natural functional walking characteristics are captured, rather than those experienced in artificial or observed settings. To better understand the extent to which setting influences gait patterns, and particularly whether observation plays a varying role on subjects of different ages, the current study investigates to what extent people walk differently in lab versus real-world environments and whether age dependencies exist. METHODS: The walking patterns of 20 young and 20 elderly healthy subjects were recorded with five wearable inertial measurement units (ZurichMOVE sensors) attached to both ankles, both wrists and the chest. An automated detection process based on dynamic time warping was developed to efficiently identify the relevant sequences. From the ZurichMOVE recordings, 15 spatio-temporal gait parameters were extracted, analyzed and compared between motion patterns captured in a controlled lab environment (10 m walking test) and the non-controlled ecologically valid real-world environment (72 h recording) in both groups. RESULTS: Several parameters (Cluster A) showed significant differences between the two environments for both groups, including an increased outward foot rotation, step width, number of steps per 180° turn, stance to swing ratio, and cycle time deviation in the real-world. A number of parameters (Cluster B) showed only significant differences between the two environments for elderly subjects, including a decreased gait velocity (p = 0.0072), decreased cadence (p = 0.0051) and increased cycle time (p = 0.0051) in real-world settings. Importantly, the real-world environment increased the differences in several parameters between the young and elderly groups. CONCLUSION: Elderly test subjects walked differently in controlled lab settings compared to their real-world environments, which indicates the need to better understand natural walking patterns under ecologically valid conditions before clinically relevant conclusions can be drawn on a subject’s functional status. Moreover, the greater inter-group differences in real-world environments seem promising regarding the sensitive identification of subjects with indications of a walking disorder. |
format | Online Article Text |
id | pubmed-7044412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-70444122020-03-09 Wearable Inertial Measurement Units for Assessing Gait in Real-World Environments Renggli, David Graf, Christina Tachatos, Nikolaos Singh, Navrag Meboldt, Mirko Taylor, William R. Stieglitz, Lennart Schmid Daners, Marianne Front Physiol Physiology BACKGROUND: Walking patterns can provide important indications of a person’s health status and be beneficial in the early diagnosis of individuals with a potential walking disorder. For appropriate gait analysis, it is critical that natural functional walking characteristics are captured, rather than those experienced in artificial or observed settings. To better understand the extent to which setting influences gait patterns, and particularly whether observation plays a varying role on subjects of different ages, the current study investigates to what extent people walk differently in lab versus real-world environments and whether age dependencies exist. METHODS: The walking patterns of 20 young and 20 elderly healthy subjects were recorded with five wearable inertial measurement units (ZurichMOVE sensors) attached to both ankles, both wrists and the chest. An automated detection process based on dynamic time warping was developed to efficiently identify the relevant sequences. From the ZurichMOVE recordings, 15 spatio-temporal gait parameters were extracted, analyzed and compared between motion patterns captured in a controlled lab environment (10 m walking test) and the non-controlled ecologically valid real-world environment (72 h recording) in both groups. RESULTS: Several parameters (Cluster A) showed significant differences between the two environments for both groups, including an increased outward foot rotation, step width, number of steps per 180° turn, stance to swing ratio, and cycle time deviation in the real-world. A number of parameters (Cluster B) showed only significant differences between the two environments for elderly subjects, including a decreased gait velocity (p = 0.0072), decreased cadence (p = 0.0051) and increased cycle time (p = 0.0051) in real-world settings. Importantly, the real-world environment increased the differences in several parameters between the young and elderly groups. CONCLUSION: Elderly test subjects walked differently in controlled lab settings compared to their real-world environments, which indicates the need to better understand natural walking patterns under ecologically valid conditions before clinically relevant conclusions can be drawn on a subject’s functional status. Moreover, the greater inter-group differences in real-world environments seem promising regarding the sensitive identification of subjects with indications of a walking disorder. Frontiers Media S.A. 2020-02-20 /pmc/articles/PMC7044412/ /pubmed/32153420 http://dx.doi.org/10.3389/fphys.2020.00090 Text en Copyright © 2020 Renggli, Graf, Tachatos, Singh, Meboldt, Taylor, Stieglitz and Schmid Daners. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Renggli, David Graf, Christina Tachatos, Nikolaos Singh, Navrag Meboldt, Mirko Taylor, William R. Stieglitz, Lennart Schmid Daners, Marianne Wearable Inertial Measurement Units for Assessing Gait in Real-World Environments |
title | Wearable Inertial Measurement Units for Assessing Gait in Real-World Environments |
title_full | Wearable Inertial Measurement Units for Assessing Gait in Real-World Environments |
title_fullStr | Wearable Inertial Measurement Units for Assessing Gait in Real-World Environments |
title_full_unstemmed | Wearable Inertial Measurement Units for Assessing Gait in Real-World Environments |
title_short | Wearable Inertial Measurement Units for Assessing Gait in Real-World Environments |
title_sort | wearable inertial measurement units for assessing gait in real-world environments |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7044412/ https://www.ncbi.nlm.nih.gov/pubmed/32153420 http://dx.doi.org/10.3389/fphys.2020.00090 |
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