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Advanced analytical methods to assess physical activity behavior using accelerometer time series: A scoping review

Physical activity (PA) is a complex human behavior, which implies that multiple dimensions need to be taken into account in order to reveal a complete picture of the PA behavior profile of an individual. This scoping review aimed to map advanced analytical methods and their summary variables, herein...

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Autores principales: Backes, Anne, Gupta, Tripti, Schmitz, Susanne, Fagherazzi, Guy, van Hees, Vincent, Malisoux, Laurent
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9298329/
https://www.ncbi.nlm.nih.gov/pubmed/34695249
http://dx.doi.org/10.1111/sms.14085
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author Backes, Anne
Gupta, Tripti
Schmitz, Susanne
Fagherazzi, Guy
van Hees, Vincent
Malisoux, Laurent
author_facet Backes, Anne
Gupta, Tripti
Schmitz, Susanne
Fagherazzi, Guy
van Hees, Vincent
Malisoux, Laurent
author_sort Backes, Anne
collection PubMed
description Physical activity (PA) is a complex human behavior, which implies that multiple dimensions need to be taken into account in order to reveal a complete picture of the PA behavior profile of an individual. This scoping review aimed to map advanced analytical methods and their summary variables, hereinafter referred to as wearable‐specific indicators of PA behavior (WIPAB), used to assess PA behavior. The strengths and limitations of those indicators as well as potential associations with certain health‐related factors were also investigated. Three databases (MEDLINE, Embase, and Web of Science) were screened for articles published in English between January 2010 and April 2020. Articles, which assessed the PA behavior, gathered objective measures of PA using tri‐axial accelerometers, and investigated WIPAB, were selected. All studies reporting WIPAB in the context of PA monitoring were synthesized and presented in four summary tables: study characteristics, details of the WIPAB, strengths, and limitations, and measures of association between those indicators and health‐related factors. In total, 7247 records were identified, of which 24 articles were included after assessing titles, abstracts, and full texts. Thirteen WIPAB were identified, which can be classified into three different categories specifically focusing on (1) the activity intensity distribution, (2) activity accumulation, and (3) the temporal correlation and regularity of the acceleration signal. Only five of the thirteen WIPAB identified in this review have been used in the literature so far to investigate the relationship between PA behavior and health, while they may provide useful additional information to the conventional PA variables.
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spelling pubmed-92983292022-07-21 Advanced analytical methods to assess physical activity behavior using accelerometer time series: A scoping review Backes, Anne Gupta, Tripti Schmitz, Susanne Fagherazzi, Guy van Hees, Vincent Malisoux, Laurent Scand J Med Sci Sports Reviews Physical activity (PA) is a complex human behavior, which implies that multiple dimensions need to be taken into account in order to reveal a complete picture of the PA behavior profile of an individual. This scoping review aimed to map advanced analytical methods and their summary variables, hereinafter referred to as wearable‐specific indicators of PA behavior (WIPAB), used to assess PA behavior. The strengths and limitations of those indicators as well as potential associations with certain health‐related factors were also investigated. Three databases (MEDLINE, Embase, and Web of Science) were screened for articles published in English between January 2010 and April 2020. Articles, which assessed the PA behavior, gathered objective measures of PA using tri‐axial accelerometers, and investigated WIPAB, were selected. All studies reporting WIPAB in the context of PA monitoring were synthesized and presented in four summary tables: study characteristics, details of the WIPAB, strengths, and limitations, and measures of association between those indicators and health‐related factors. In total, 7247 records were identified, of which 24 articles were included after assessing titles, abstracts, and full texts. Thirteen WIPAB were identified, which can be classified into three different categories specifically focusing on (1) the activity intensity distribution, (2) activity accumulation, and (3) the temporal correlation and regularity of the acceleration signal. Only five of the thirteen WIPAB identified in this review have been used in the literature so far to investigate the relationship between PA behavior and health, while they may provide useful additional information to the conventional PA variables. John Wiley and Sons Inc. 2021-11-01 2022-01 /pmc/articles/PMC9298329/ /pubmed/34695249 http://dx.doi.org/10.1111/sms.14085 Text en © 2021 The Authors. Scandinavian Journal of Medicine & Science In Sports published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Reviews
Backes, Anne
Gupta, Tripti
Schmitz, Susanne
Fagherazzi, Guy
van Hees, Vincent
Malisoux, Laurent
Advanced analytical methods to assess physical activity behavior using accelerometer time series: A scoping review
title Advanced analytical methods to assess physical activity behavior using accelerometer time series: A scoping review
title_full Advanced analytical methods to assess physical activity behavior using accelerometer time series: A scoping review
title_fullStr Advanced analytical methods to assess physical activity behavior using accelerometer time series: A scoping review
title_full_unstemmed Advanced analytical methods to assess physical activity behavior using accelerometer time series: A scoping review
title_short Advanced analytical methods to assess physical activity behavior using accelerometer time series: A scoping review
title_sort advanced analytical methods to assess physical activity behavior using accelerometer time series: a scoping review
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9298329/
https://www.ncbi.nlm.nih.gov/pubmed/34695249
http://dx.doi.org/10.1111/sms.14085
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