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Pilot Study of the EncephaLog Smartphone Application for Gait Analysis
Gait disorders and falls are common in elders and in many clinical conditions, yet they are typically infrequently and subjectively evaluated, limiting prevention and intervention. Completion-time of the Timed-Up-and-Go (TUG) test is a well-accepted clinical biomarker for rating mobility and predict...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929058/ https://www.ncbi.nlm.nih.gov/pubmed/31779224 http://dx.doi.org/10.3390/s19235179 |
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author | Tchelet, Keren Stark-Inbar, Alit Yekutieli, Ziv |
author_facet | Tchelet, Keren Stark-Inbar, Alit Yekutieli, Ziv |
author_sort | Tchelet, Keren |
collection | PubMed |
description | Gait disorders and falls are common in elders and in many clinical conditions, yet they are typically infrequently and subjectively evaluated, limiting prevention and intervention. Completion-time of the Timed-Up-and-Go (TUG) test is a well-accepted clinical biomarker for rating mobility and prediction of falls risk. Using smartphones’ integral accelerometers and gyroscopes, we already demonstrated that TUG completion-time can be accurately measured via a smartphone app. Here we present an extended app, EncephaLog(TM), which provides gait analysis in much more detail, offering 9 additional gait biomarkers on top of the TUG completion-time. In this pilot, four healthy adults participated in a total of 32 TUG tests; simultaneously recorded by EncephaLog and motion sensor devices used in movement labs: motion capture cameras (MCC), pressure mat; and/or wearable sensors. Results show high agreement between EncephaLog biomarkers and those measured by the other devices. These preliminary results suggest that EncephaLog can provide an accurate, yet simpler, instrumented TUG (iTUG) platform than existing alternatives, offering a solution for clinics that cannot afford the cost or space required for a dedicated motion lab and for monitoring patients at their homes. Further research on a larger study population with pathologies is required to assess full validity. |
format | Online Article Text |
id | pubmed-6929058 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-69290582019-12-26 Pilot Study of the EncephaLog Smartphone Application for Gait Analysis Tchelet, Keren Stark-Inbar, Alit Yekutieli, Ziv Sensors (Basel) Article Gait disorders and falls are common in elders and in many clinical conditions, yet they are typically infrequently and subjectively evaluated, limiting prevention and intervention. Completion-time of the Timed-Up-and-Go (TUG) test is a well-accepted clinical biomarker for rating mobility and prediction of falls risk. Using smartphones’ integral accelerometers and gyroscopes, we already demonstrated that TUG completion-time can be accurately measured via a smartphone app. Here we present an extended app, EncephaLog(TM), which provides gait analysis in much more detail, offering 9 additional gait biomarkers on top of the TUG completion-time. In this pilot, four healthy adults participated in a total of 32 TUG tests; simultaneously recorded by EncephaLog and motion sensor devices used in movement labs: motion capture cameras (MCC), pressure mat; and/or wearable sensors. Results show high agreement between EncephaLog biomarkers and those measured by the other devices. These preliminary results suggest that EncephaLog can provide an accurate, yet simpler, instrumented TUG (iTUG) platform than existing alternatives, offering a solution for clinics that cannot afford the cost or space required for a dedicated motion lab and for monitoring patients at their homes. Further research on a larger study population with pathologies is required to assess full validity. MDPI 2019-11-26 /pmc/articles/PMC6929058/ /pubmed/31779224 http://dx.doi.org/10.3390/s19235179 Text en © 2019 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 Tchelet, Keren Stark-Inbar, Alit Yekutieli, Ziv Pilot Study of the EncephaLog Smartphone Application for Gait Analysis |
title | Pilot Study of the EncephaLog Smartphone Application for Gait Analysis |
title_full | Pilot Study of the EncephaLog Smartphone Application for Gait Analysis |
title_fullStr | Pilot Study of the EncephaLog Smartphone Application for Gait Analysis |
title_full_unstemmed | Pilot Study of the EncephaLog Smartphone Application for Gait Analysis |
title_short | Pilot Study of the EncephaLog Smartphone Application for Gait Analysis |
title_sort | pilot study of the encephalog smartphone application for gait analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929058/ https://www.ncbi.nlm.nih.gov/pubmed/31779224 http://dx.doi.org/10.3390/s19235179 |
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