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Classifying Step and Spin Turns Using Wireless Gyroscopes and Implications for Fall Risk Assessments

Recent studies have reported a greater prevalence of spin turns, which are more unstable than step turns, in older adults compared to young adults in laboratory settings. Currently, turning strategies can only be identified through visual observation, either in-person or through video. This paper pr...

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Detalles Bibliográficos
Autores principales: Fino, Peter C., Frames, Christopher W., Lockhart, Thurmon E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481922/
https://www.ncbi.nlm.nih.gov/pubmed/25954950
http://dx.doi.org/10.3390/s150510676
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author Fino, Peter C.
Frames, Christopher W.
Lockhart, Thurmon E.
author_facet Fino, Peter C.
Frames, Christopher W.
Lockhart, Thurmon E.
author_sort Fino, Peter C.
collection PubMed
description Recent studies have reported a greater prevalence of spin turns, which are more unstable than step turns, in older adults compared to young adults in laboratory settings. Currently, turning strategies can only be identified through visual observation, either in-person or through video. This paper presents two unique methods and their combination to remotely monitor turning behavior using three uniaxial gyroscopes. Five young adults performed 90° turns at slow, normal, and fast walking speeds around a variety of obstacles while instrumented with three IMUs (attached on the trunk, left and right shank). Raw data from 360 trials were analyzed. Compared to visual classification, the two IMU methods’ sensitivity/specificity to detecting spin turns were 76.1%/76.7% and 76.1%/84.4%, respectively. When the two methods were combined, the IMU had an overall 86.8% sensitivity and 92.2% specificity, with 89.4%/100% sensitivity/specificity at slow speeds. This combined method can be implemented into wireless fall prevention systems and used to identify increased use of spin turns. This method allows for longitudinal monitoring of turning strategies and allows researchers to test for potential associations between the frequency of spin turns and clinically relevant outcomes (e.g., falls) in non-laboratory settings.
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spelling pubmed-44819222015-06-29 Classifying Step and Spin Turns Using Wireless Gyroscopes and Implications for Fall Risk Assessments Fino, Peter C. Frames, Christopher W. Lockhart, Thurmon E. Sensors (Basel) Article Recent studies have reported a greater prevalence of spin turns, which are more unstable than step turns, in older adults compared to young adults in laboratory settings. Currently, turning strategies can only be identified through visual observation, either in-person or through video. This paper presents two unique methods and their combination to remotely monitor turning behavior using three uniaxial gyroscopes. Five young adults performed 90° turns at slow, normal, and fast walking speeds around a variety of obstacles while instrumented with three IMUs (attached on the trunk, left and right shank). Raw data from 360 trials were analyzed. Compared to visual classification, the two IMU methods’ sensitivity/specificity to detecting spin turns were 76.1%/76.7% and 76.1%/84.4%, respectively. When the two methods were combined, the IMU had an overall 86.8% sensitivity and 92.2% specificity, with 89.4%/100% sensitivity/specificity at slow speeds. This combined method can be implemented into wireless fall prevention systems and used to identify increased use of spin turns. This method allows for longitudinal monitoring of turning strategies and allows researchers to test for potential associations between the frequency of spin turns and clinically relevant outcomes (e.g., falls) in non-laboratory settings. MDPI 2015-05-06 /pmc/articles/PMC4481922/ /pubmed/25954950 http://dx.doi.org/10.3390/s150510676 Text en © 2015 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 license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Fino, Peter C.
Frames, Christopher W.
Lockhart, Thurmon E.
Classifying Step and Spin Turns Using Wireless Gyroscopes and Implications for Fall Risk Assessments
title Classifying Step and Spin Turns Using Wireless Gyroscopes and Implications for Fall Risk Assessments
title_full Classifying Step and Spin Turns Using Wireless Gyroscopes and Implications for Fall Risk Assessments
title_fullStr Classifying Step and Spin Turns Using Wireless Gyroscopes and Implications for Fall Risk Assessments
title_full_unstemmed Classifying Step and Spin Turns Using Wireless Gyroscopes and Implications for Fall Risk Assessments
title_short Classifying Step and Spin Turns Using Wireless Gyroscopes and Implications for Fall Risk Assessments
title_sort classifying step and spin turns using wireless gyroscopes and implications for fall risk assessments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481922/
https://www.ncbi.nlm.nih.gov/pubmed/25954950
http://dx.doi.org/10.3390/s150510676
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