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Cross-Comparisons of Gait Speeds by Automatic Sensors and a Stopwatch to Provide Converting Formula Between Measuring Modalities

BACKGROUND: We aimed to compare 4 automatic devices with a conventional stopwatch for measuring gait speed. METHODS: We used 4 experimental devices to automatically measure gait speed: 1) Gaitspeedometer (GSM) 1, with laser sensors; 2) GSM2, with ultrasound sensors; 3) GSM3, with infrared sensors; a...

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Autores principales: Jung, Hee-Won, Roh, Hyun-Chul, Kim, Sun-wook, Kim, Sunyoung, Kim, Miji, Won, Chang Won
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Geriatrics Society 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7387595/
https://www.ncbi.nlm.nih.gov/pubmed/32743291
http://dx.doi.org/10.4235/agmr.19.0016
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author Jung, Hee-Won
Roh, Hyun-Chul
Kim, Sun-wook
Kim, Sunyoung
Kim, Miji
Won, Chang Won
author_facet Jung, Hee-Won
Roh, Hyun-Chul
Kim, Sun-wook
Kim, Sunyoung
Kim, Miji
Won, Chang Won
author_sort Jung, Hee-Won
collection PubMed
description BACKGROUND: We aimed to compare 4 automatic devices with a conventional stopwatch for measuring gait speed. METHODS: We used 4 experimental devices to automatically measure gait speed: 1) Gaitspeedometer (GSM) 1, with laser sensors; 2) GSM2, with ultrasound sensors; 3) GSM3, with infrared sensors; and 4) GSM4, with a light detection and ranging sensor. To assess compatibility between different versions of GSMs, we collected 426 data points from 4 young engineers walking at random speeds and with varying postures. We used these data to convert gait speed measured by GSM1 and 2 for compatibility with GSM3 in the Korean Frailty and Aging Cohort Study (KFACS) dataset. RESULTS: Mean gait speeds measured with GSMs 1–4 were 1.7% slower (R(2)=0.997), 12.2% faster (R(2)=0.993), 1.3% slower (R(2)=0.999), and 4.3% slower (R(2)=0.996), respectively, than the gait speed measured with a stopwatch. The concordance correlation coefficient between each GSM and the stopwatch was higher than 0.9. Using linear regression analysis with no constant term, conversion formulas for GSMs were established for the KFACS dataset using GSM1 and GSM2. CONCLUSION: The 4 methods of automatic gait speed measurement and the manually measured gait speed correlated well with each other, and we hope these new technologies reduce barriers to measuring older people’s gait speed in busy clinical settings.
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spelling pubmed-73875952020-07-30 Cross-Comparisons of Gait Speeds by Automatic Sensors and a Stopwatch to Provide Converting Formula Between Measuring Modalities Jung, Hee-Won Roh, Hyun-Chul Kim, Sun-wook Kim, Sunyoung Kim, Miji Won, Chang Won Ann Geriatr Med Res Original Article BACKGROUND: We aimed to compare 4 automatic devices with a conventional stopwatch for measuring gait speed. METHODS: We used 4 experimental devices to automatically measure gait speed: 1) Gaitspeedometer (GSM) 1, with laser sensors; 2) GSM2, with ultrasound sensors; 3) GSM3, with infrared sensors; and 4) GSM4, with a light detection and ranging sensor. To assess compatibility between different versions of GSMs, we collected 426 data points from 4 young engineers walking at random speeds and with varying postures. We used these data to convert gait speed measured by GSM1 and 2 for compatibility with GSM3 in the Korean Frailty and Aging Cohort Study (KFACS) dataset. RESULTS: Mean gait speeds measured with GSMs 1–4 were 1.7% slower (R(2)=0.997), 12.2% faster (R(2)=0.993), 1.3% slower (R(2)=0.999), and 4.3% slower (R(2)=0.996), respectively, than the gait speed measured with a stopwatch. The concordance correlation coefficient between each GSM and the stopwatch was higher than 0.9. Using linear regression analysis with no constant term, conversion formulas for GSMs were established for the KFACS dataset using GSM1 and GSM2. CONCLUSION: The 4 methods of automatic gait speed measurement and the manually measured gait speed correlated well with each other, and we hope these new technologies reduce barriers to measuring older people’s gait speed in busy clinical settings. Korean Geriatrics Society 2019-06 2019-06-30 /pmc/articles/PMC7387595/ /pubmed/32743291 http://dx.doi.org/10.4235/agmr.19.0016 Text en Copyright © 2019 by The Korean Geriatric Society This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Jung, Hee-Won
Roh, Hyun-Chul
Kim, Sun-wook
Kim, Sunyoung
Kim, Miji
Won, Chang Won
Cross-Comparisons of Gait Speeds by Automatic Sensors and a Stopwatch to Provide Converting Formula Between Measuring Modalities
title Cross-Comparisons of Gait Speeds by Automatic Sensors and a Stopwatch to Provide Converting Formula Between Measuring Modalities
title_full Cross-Comparisons of Gait Speeds by Automatic Sensors and a Stopwatch to Provide Converting Formula Between Measuring Modalities
title_fullStr Cross-Comparisons of Gait Speeds by Automatic Sensors and a Stopwatch to Provide Converting Formula Between Measuring Modalities
title_full_unstemmed Cross-Comparisons of Gait Speeds by Automatic Sensors and a Stopwatch to Provide Converting Formula Between Measuring Modalities
title_short Cross-Comparisons of Gait Speeds by Automatic Sensors and a Stopwatch to Provide Converting Formula Between Measuring Modalities
title_sort cross-comparisons of gait speeds by automatic sensors and a stopwatch to provide converting formula between measuring modalities
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7387595/
https://www.ncbi.nlm.nih.gov/pubmed/32743291
http://dx.doi.org/10.4235/agmr.19.0016
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