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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Geriatrics Society
2019
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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. |
format | Online Article Text |
id | pubmed-7387595 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Korean Geriatrics Society |
record_format | MEDLINE/PubMed |
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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