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Association between Self-Reported Prior Night’s Sleep and Single-Task Gait in Healthy, Young Adults: A Study Using Machine Learning

Failure to obtain the recommended 7–9 h of sleep has been associated with injuries in youth and adults. However, most research on the influence of prior night’s sleep and gait has been conducted on older adults and clinical populations. Therefore, the objective of this study was to identify individu...

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Autores principales: Boolani, Ali, Martin, Joel, Huang, Haikun, Yu, Lap-Fai, Stark, Maggie, Grin, Zachary, Roy, Marissa, Yager, Chelsea, Teymouri, Seema, Bradley, Dylan, Martin, Rebecca, Fulk, George, Kakar, Rumit Singh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572361/
https://www.ncbi.nlm.nih.gov/pubmed/36236511
http://dx.doi.org/10.3390/s22197406
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author Boolani, Ali
Martin, Joel
Huang, Haikun
Yu, Lap-Fai
Stark, Maggie
Grin, Zachary
Roy, Marissa
Yager, Chelsea
Teymouri, Seema
Bradley, Dylan
Martin, Rebecca
Fulk, George
Kakar, Rumit Singh
author_facet Boolani, Ali
Martin, Joel
Huang, Haikun
Yu, Lap-Fai
Stark, Maggie
Grin, Zachary
Roy, Marissa
Yager, Chelsea
Teymouri, Seema
Bradley, Dylan
Martin, Rebecca
Fulk, George
Kakar, Rumit Singh
author_sort Boolani, Ali
collection PubMed
description Failure to obtain the recommended 7–9 h of sleep has been associated with injuries in youth and adults. However, most research on the influence of prior night’s sleep and gait has been conducted on older adults and clinical populations. Therefore, the objective of this study was to identify individuals who experience partial sleep deprivation and/or sleep extension the prior night using single task gait. Participants (n = 123, age 24.3 ± 4.0 years; 65% female) agreed to participate in this study. Self-reported sleep duration of the night prior to testing was collected. Gait data was collected with inertial sensors during a 2 min walk test. Group differences (<7 h and >9 h, poor sleepers; 7–9 h, good sleepers) in gait characteristics were assessed using machine learning and a post-hoc ANCOVA. Results indicated a correlation (r = 0.79) between gait parameters and prior night’s sleep. The most accurate machine learning model was a Random Forest Classifier using the top 9 features, which had a mean accuracy of 65.03%. Our findings suggest that good sleepers had more asymmetrical gait patterns and were better at maintaining gait speed than poor sleepers. Further research with larger subject sizes is needed to develop more accurate machine learning models to identify prior night’s sleep using single-task gait.
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spelling pubmed-95723612022-10-17 Association between Self-Reported Prior Night’s Sleep and Single-Task Gait in Healthy, Young Adults: A Study Using Machine Learning Boolani, Ali Martin, Joel Huang, Haikun Yu, Lap-Fai Stark, Maggie Grin, Zachary Roy, Marissa Yager, Chelsea Teymouri, Seema Bradley, Dylan Martin, Rebecca Fulk, George Kakar, Rumit Singh Sensors (Basel) Article Failure to obtain the recommended 7–9 h of sleep has been associated with injuries in youth and adults. However, most research on the influence of prior night’s sleep and gait has been conducted on older adults and clinical populations. Therefore, the objective of this study was to identify individuals who experience partial sleep deprivation and/or sleep extension the prior night using single task gait. Participants (n = 123, age 24.3 ± 4.0 years; 65% female) agreed to participate in this study. Self-reported sleep duration of the night prior to testing was collected. Gait data was collected with inertial sensors during a 2 min walk test. Group differences (<7 h and >9 h, poor sleepers; 7–9 h, good sleepers) in gait characteristics were assessed using machine learning and a post-hoc ANCOVA. Results indicated a correlation (r = 0.79) between gait parameters and prior night’s sleep. The most accurate machine learning model was a Random Forest Classifier using the top 9 features, which had a mean accuracy of 65.03%. Our findings suggest that good sleepers had more asymmetrical gait patterns and were better at maintaining gait speed than poor sleepers. Further research with larger subject sizes is needed to develop more accurate machine learning models to identify prior night’s sleep using single-task gait. MDPI 2022-09-29 /pmc/articles/PMC9572361/ /pubmed/36236511 http://dx.doi.org/10.3390/s22197406 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Boolani, Ali
Martin, Joel
Huang, Haikun
Yu, Lap-Fai
Stark, Maggie
Grin, Zachary
Roy, Marissa
Yager, Chelsea
Teymouri, Seema
Bradley, Dylan
Martin, Rebecca
Fulk, George
Kakar, Rumit Singh
Association between Self-Reported Prior Night’s Sleep and Single-Task Gait in Healthy, Young Adults: A Study Using Machine Learning
title Association between Self-Reported Prior Night’s Sleep and Single-Task Gait in Healthy, Young Adults: A Study Using Machine Learning
title_full Association between Self-Reported Prior Night’s Sleep and Single-Task Gait in Healthy, Young Adults: A Study Using Machine Learning
title_fullStr Association between Self-Reported Prior Night’s Sleep and Single-Task Gait in Healthy, Young Adults: A Study Using Machine Learning
title_full_unstemmed Association between Self-Reported Prior Night’s Sleep and Single-Task Gait in Healthy, Young Adults: A Study Using Machine Learning
title_short Association between Self-Reported Prior Night’s Sleep and Single-Task Gait in Healthy, Young Adults: A Study Using Machine Learning
title_sort association between self-reported prior night’s sleep and single-task gait in healthy, young adults: a study using machine learning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572361/
https://www.ncbi.nlm.nih.gov/pubmed/36236511
http://dx.doi.org/10.3390/s22197406
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