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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...

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Detalles Bibliográficos
Autores principales: Tchelet, Keren, Stark-Inbar, Alit, Yekutieli, Ziv
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
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.
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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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