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Prescribing Personalized Exercise Programs Using Smartphone Sensors For Remote Fitness Assessment
Guidelines for physical activity emphasize multiple fitness components among people aged >65. The age-related increase in variability of fitness components necessitates accurate individualized assessment prior to optimal prescription for personalized exercise program. Accordingly, we tested feasi...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8681662/ http://dx.doi.org/10.1093/geroni/igab046.3256 |
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author | Jacobs, Jeremy Yekutiel, Ziv Arnon, Mical Argov, Esther Karlinsky, Keren Tchelet Benmoha, Eti Netz, yael |
author_facet | Jacobs, Jeremy Yekutiel, Ziv Arnon, Mical Argov, Esther Karlinsky, Keren Tchelet Benmoha, Eti Netz, yael |
author_sort | Jacobs, Jeremy |
collection | PubMed |
description | Guidelines for physical activity emphasize multiple fitness components among people aged >65. The age-related increase in variability of fitness components necessitates accurate individualized assessment prior to optimal prescription for personalized exercise program. Accordingly, we tested feasibility and effectiveness of a novel tool designed to remotely assess balance, flexibility, and strength using smartphone sensors (accelerometer/gyroscope), and subsequently remotely deliver personalized exercise programs via smartphone. This pilot study enrolled 52 healthy volunteers (34 females) aged 65+, with normal cognition and low fall-risk. Baseline preliminary data from smartphone fitness assessment were analyzed to generate 42 fitness digital-markers, used to generate personalized exercise programs (5 times/week for 6 weeks). Programs included graded exercises for upper/lower body, flexibility, strength, and balance (dynamic, static, vestibular). Fitness was remotely assessed at baseline and after six weeks. Average age was 74.7±6.4 years; adherence was 3.6±1.7 exercise sessions/week. Significant improvement for pre/post testing was observed for 10/12 digital-markers of strength/flexibility for upper/lower body (sit-to-stand repetitions/duration; arm-lift duration; torso-rotation; arm-extension/flexion). Balance improved significantly for 6/10 measures of tandem-stance, with consistent (non-significant) trends observed across 20 balance digital-markers of tandem-walk and one leg-stance. Balance showed greatest improvement among the 37 participants exercising ≥3/week. These preliminary results serve as proof of concept among people aged >65: high adherence and improved fitness confirm the potential benefits and niche for remote fitness assessment used to generate personalized exercise programs. Future research is required to confirm the benefits among specific patient groups, such as those with frailty, deconditioning, cognitive and functional impairment. |
format | Online Article Text |
id | pubmed-8681662 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-86816622021-12-17 Prescribing Personalized Exercise Programs Using Smartphone Sensors For Remote Fitness Assessment Jacobs, Jeremy Yekutiel, Ziv Arnon, Mical Argov, Esther Karlinsky, Keren Tchelet Benmoha, Eti Netz, yael Innov Aging Abstracts Guidelines for physical activity emphasize multiple fitness components among people aged >65. The age-related increase in variability of fitness components necessitates accurate individualized assessment prior to optimal prescription for personalized exercise program. Accordingly, we tested feasibility and effectiveness of a novel tool designed to remotely assess balance, flexibility, and strength using smartphone sensors (accelerometer/gyroscope), and subsequently remotely deliver personalized exercise programs via smartphone. This pilot study enrolled 52 healthy volunteers (34 females) aged 65+, with normal cognition and low fall-risk. Baseline preliminary data from smartphone fitness assessment were analyzed to generate 42 fitness digital-markers, used to generate personalized exercise programs (5 times/week for 6 weeks). Programs included graded exercises for upper/lower body, flexibility, strength, and balance (dynamic, static, vestibular). Fitness was remotely assessed at baseline and after six weeks. Average age was 74.7±6.4 years; adherence was 3.6±1.7 exercise sessions/week. Significant improvement for pre/post testing was observed for 10/12 digital-markers of strength/flexibility for upper/lower body (sit-to-stand repetitions/duration; arm-lift duration; torso-rotation; arm-extension/flexion). Balance improved significantly for 6/10 measures of tandem-stance, with consistent (non-significant) trends observed across 20 balance digital-markers of tandem-walk and one leg-stance. Balance showed greatest improvement among the 37 participants exercising ≥3/week. These preliminary results serve as proof of concept among people aged >65: high adherence and improved fitness confirm the potential benefits and niche for remote fitness assessment used to generate personalized exercise programs. Future research is required to confirm the benefits among specific patient groups, such as those with frailty, deconditioning, cognitive and functional impairment. Oxford University Press 2021-12-17 /pmc/articles/PMC8681662/ http://dx.doi.org/10.1093/geroni/igab046.3256 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Abstracts Jacobs, Jeremy Yekutiel, Ziv Arnon, Mical Argov, Esther Karlinsky, Keren Tchelet Benmoha, Eti Netz, yael Prescribing Personalized Exercise Programs Using Smartphone Sensors For Remote Fitness Assessment |
title | Prescribing Personalized Exercise Programs Using Smartphone Sensors For Remote Fitness Assessment |
title_full | Prescribing Personalized Exercise Programs Using Smartphone Sensors For Remote Fitness Assessment |
title_fullStr | Prescribing Personalized Exercise Programs Using Smartphone Sensors For Remote Fitness Assessment |
title_full_unstemmed | Prescribing Personalized Exercise Programs Using Smartphone Sensors For Remote Fitness Assessment |
title_short | Prescribing Personalized Exercise Programs Using Smartphone Sensors For Remote Fitness Assessment |
title_sort | prescribing personalized exercise programs using smartphone sensors for remote fitness assessment |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8681662/ http://dx.doi.org/10.1093/geroni/igab046.3256 |
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