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The Role of Wearable Sensors to Monitor Physical Activity and Sleep Patterns in Older Adult Inpatients: A Structured Review
Low levels of physical activity (PA) and sleep disruption are commonly seen in older adult inpatients and are associated with poor health outcomes. Wearable sensors allow for objective continuous monitoring; however, there is no consensus as to how wearable sensors should be implemented. This review...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222486/ https://www.ncbi.nlm.nih.gov/pubmed/37430796 http://dx.doi.org/10.3390/s23104881 |
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author | Bate, Gemma L. Kirk, Cameron Rehman, Rana Z. U. Guan, Yu Yarnall, Alison J. Del Din, Silvia Lawson, Rachael A. |
author_facet | Bate, Gemma L. Kirk, Cameron Rehman, Rana Z. U. Guan, Yu Yarnall, Alison J. Del Din, Silvia Lawson, Rachael A. |
author_sort | Bate, Gemma L. |
collection | PubMed |
description | Low levels of physical activity (PA) and sleep disruption are commonly seen in older adult inpatients and are associated with poor health outcomes. Wearable sensors allow for objective continuous monitoring; however, there is no consensus as to how wearable sensors should be implemented. This review aimed to provide an overview of the use of wearable sensors in older adult inpatient populations, including models used, body placement and outcome measures. Five databases were searched; 89 articles met inclusion criteria. We found that studies used heterogenous methods, including a variety of sensor models, placement and outcome measures. Most studies reported the use of only one sensor, with either the wrist or thigh being the preferred location in PA studies and the wrist for sleep outcomes. The reported PA measures can be mostly characterised as the frequency and duration of PA (Volume) with fewer measures relating to intensity (rate of magnitude) and pattern of activity (distribution per day/week). Sleep and circadian rhythm measures were reported less frequently with a limited number of studies providing both physical activity and sleep/circadian rhythm outcomes concurrently. This review provides recommendations for future research in older adult inpatient populations. With protocols of best practice, wearable sensors could facilitate the monitoring of inpatient recovery and provide measures to inform participant stratification and establish common objective endpoints across clinical trials. |
format | Online Article Text |
id | pubmed-10222486 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102224862023-05-28 The Role of Wearable Sensors to Monitor Physical Activity and Sleep Patterns in Older Adult Inpatients: A Structured Review Bate, Gemma L. Kirk, Cameron Rehman, Rana Z. U. Guan, Yu Yarnall, Alison J. Del Din, Silvia Lawson, Rachael A. Sensors (Basel) Review Low levels of physical activity (PA) and sleep disruption are commonly seen in older adult inpatients and are associated with poor health outcomes. Wearable sensors allow for objective continuous monitoring; however, there is no consensus as to how wearable sensors should be implemented. This review aimed to provide an overview of the use of wearable sensors in older adult inpatient populations, including models used, body placement and outcome measures. Five databases were searched; 89 articles met inclusion criteria. We found that studies used heterogenous methods, including a variety of sensor models, placement and outcome measures. Most studies reported the use of only one sensor, with either the wrist or thigh being the preferred location in PA studies and the wrist for sleep outcomes. The reported PA measures can be mostly characterised as the frequency and duration of PA (Volume) with fewer measures relating to intensity (rate of magnitude) and pattern of activity (distribution per day/week). Sleep and circadian rhythm measures were reported less frequently with a limited number of studies providing both physical activity and sleep/circadian rhythm outcomes concurrently. This review provides recommendations for future research in older adult inpatient populations. With protocols of best practice, wearable sensors could facilitate the monitoring of inpatient recovery and provide measures to inform participant stratification and establish common objective endpoints across clinical trials. MDPI 2023-05-18 /pmc/articles/PMC10222486/ /pubmed/37430796 http://dx.doi.org/10.3390/s23104881 Text en © 2023 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 | Review Bate, Gemma L. Kirk, Cameron Rehman, Rana Z. U. Guan, Yu Yarnall, Alison J. Del Din, Silvia Lawson, Rachael A. The Role of Wearable Sensors to Monitor Physical Activity and Sleep Patterns in Older Adult Inpatients: A Structured Review |
title | The Role of Wearable Sensors to Monitor Physical Activity and Sleep Patterns in Older Adult Inpatients: A Structured Review |
title_full | The Role of Wearable Sensors to Monitor Physical Activity and Sleep Patterns in Older Adult Inpatients: A Structured Review |
title_fullStr | The Role of Wearable Sensors to Monitor Physical Activity and Sleep Patterns in Older Adult Inpatients: A Structured Review |
title_full_unstemmed | The Role of Wearable Sensors to Monitor Physical Activity and Sleep Patterns in Older Adult Inpatients: A Structured Review |
title_short | The Role of Wearable Sensors to Monitor Physical Activity and Sleep Patterns in Older Adult Inpatients: A Structured Review |
title_sort | role of wearable sensors to monitor physical activity and sleep patterns in older adult inpatients: a structured review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222486/ https://www.ncbi.nlm.nih.gov/pubmed/37430796 http://dx.doi.org/10.3390/s23104881 |
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