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Advanced analytical methods to assess physical activity behaviour using accelerometer raw time series data: a protocol for a scoping review

BACKGROUND: Physical activity (PA) is a complex multidimensional human behaviour. Currently, there is no standardised approach for measuring PA using wearable accelerometers in health research. The total volume of PA is an important variable because it includes the frequency, intensity and duration...

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Autores principales: Rastogi, Tripti, Backes, Anne, Schmitz, Susanne, Fagherazzi, Guy, van Hees, Vincent, Malisoux, Laurent
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7648952/
https://www.ncbi.nlm.nih.gov/pubmed/33160413
http://dx.doi.org/10.1186/s13643-020-01515-2
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author Rastogi, Tripti
Backes, Anne
Schmitz, Susanne
Fagherazzi, Guy
van Hees, Vincent
Malisoux, Laurent
author_facet Rastogi, Tripti
Backes, Anne
Schmitz, Susanne
Fagherazzi, Guy
van Hees, Vincent
Malisoux, Laurent
author_sort Rastogi, Tripti
collection PubMed
description BACKGROUND: Physical activity (PA) is a complex multidimensional human behaviour. Currently, there is no standardised approach for measuring PA using wearable accelerometers in health research. The total volume of PA is an important variable because it includes the frequency, intensity and duration of activity bouts, but it reduces them down to a single summary variable. Therefore, analytical approaches using accelerometer raw time series data taking into account the way PA are accumulated over time may provide more clinically relevant features of physical behaviour. Advances on these fields are highly needed in the context of the rapid development of digital health studies using connected trackers and smartwatches. The objective of this review will be to map advanced analytical approaches and their multidimensional summary variables used to provide a comprehensive picture of PA behaviour. METHODS: This scoping review will be guided by the Arksey and O’Malley methodological framework. A search for relevant publications will be undertaken in MEDLINE (PubMed), Embase and Web of Science databases. The selection of articles will be limited to studies published in English from January 2010 onwards. Studies including analytical methods that go beyond total PA volume, average daily acceleration and the conventional cut-point approaches, involving tri-axial accelerometer data will be included. Two reviewers will independently screen all citations, full-text articles and extract data. The data will be collated, stored and charted to provide a descriptive summary of the analytical methods and outputs, their strengths and limitations and their association with different health outcomes. DISCUSSION: This protocol describes a systematic method to identify, map and synthesise advanced analytical approaches and their multidimensional summary variables used to investigate PA behaviour and identify potentially clinically relevant features. The results of this review will be useful to guide future research related to analysing PA patterns, investigate their association with health conditions and suggest appropriate recommendations for changes in PA behaviour. The results may be of interest to sports scientists, clinical researchers, epidemiologists and smartphone application developers in the field of PA assessment. SCOPING REVIEW REGISTRATION: This protocol has been registered with the Open Science Framework (OSF): https://osf.io/yxgmb.
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spelling pubmed-76489522020-11-09 Advanced analytical methods to assess physical activity behaviour using accelerometer raw time series data: a protocol for a scoping review Rastogi, Tripti Backes, Anne Schmitz, Susanne Fagherazzi, Guy van Hees, Vincent Malisoux, Laurent Syst Rev Protocol BACKGROUND: Physical activity (PA) is a complex multidimensional human behaviour. Currently, there is no standardised approach for measuring PA using wearable accelerometers in health research. The total volume of PA is an important variable because it includes the frequency, intensity and duration of activity bouts, but it reduces them down to a single summary variable. Therefore, analytical approaches using accelerometer raw time series data taking into account the way PA are accumulated over time may provide more clinically relevant features of physical behaviour. Advances on these fields are highly needed in the context of the rapid development of digital health studies using connected trackers and smartwatches. The objective of this review will be to map advanced analytical approaches and their multidimensional summary variables used to provide a comprehensive picture of PA behaviour. METHODS: This scoping review will be guided by the Arksey and O’Malley methodological framework. A search for relevant publications will be undertaken in MEDLINE (PubMed), Embase and Web of Science databases. The selection of articles will be limited to studies published in English from January 2010 onwards. Studies including analytical methods that go beyond total PA volume, average daily acceleration and the conventional cut-point approaches, involving tri-axial accelerometer data will be included. Two reviewers will independently screen all citations, full-text articles and extract data. The data will be collated, stored and charted to provide a descriptive summary of the analytical methods and outputs, their strengths and limitations and their association with different health outcomes. DISCUSSION: This protocol describes a systematic method to identify, map and synthesise advanced analytical approaches and their multidimensional summary variables used to investigate PA behaviour and identify potentially clinically relevant features. The results of this review will be useful to guide future research related to analysing PA patterns, investigate their association with health conditions and suggest appropriate recommendations for changes in PA behaviour. The results may be of interest to sports scientists, clinical researchers, epidemiologists and smartphone application developers in the field of PA assessment. SCOPING REVIEW REGISTRATION: This protocol has been registered with the Open Science Framework (OSF): https://osf.io/yxgmb. BioMed Central 2020-11-07 /pmc/articles/PMC7648952/ /pubmed/33160413 http://dx.doi.org/10.1186/s13643-020-01515-2 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Protocol
Rastogi, Tripti
Backes, Anne
Schmitz, Susanne
Fagherazzi, Guy
van Hees, Vincent
Malisoux, Laurent
Advanced analytical methods to assess physical activity behaviour using accelerometer raw time series data: a protocol for a scoping review
title Advanced analytical methods to assess physical activity behaviour using accelerometer raw time series data: a protocol for a scoping review
title_full Advanced analytical methods to assess physical activity behaviour using accelerometer raw time series data: a protocol for a scoping review
title_fullStr Advanced analytical methods to assess physical activity behaviour using accelerometer raw time series data: a protocol for a scoping review
title_full_unstemmed Advanced analytical methods to assess physical activity behaviour using accelerometer raw time series data: a protocol for a scoping review
title_short Advanced analytical methods to assess physical activity behaviour using accelerometer raw time series data: a protocol for a scoping review
title_sort advanced analytical methods to assess physical activity behaviour using accelerometer raw time series data: a protocol for a scoping review
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7648952/
https://www.ncbi.nlm.nih.gov/pubmed/33160413
http://dx.doi.org/10.1186/s13643-020-01515-2
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