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Calibration and validation of accelerometry to measure physical activity in adult clinical groups: A systematic review

A growing body of research calibrating and validating accelerometers to classify physical activity intensities has led to a range of cut-points. However, the applicability of current calibration protocols to clinical populations remains to be addressed. The aim of this review was to evaluate the acc...

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Autores principales: Bianchim, Mayara S, McNarry, Melitta A., Larun, Lillebeth, Mackintosh, Kelly A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6931234/
https://www.ncbi.nlm.nih.gov/pubmed/31890467
http://dx.doi.org/10.1016/j.pmedr.2019.101001
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author Bianchim, Mayara S
McNarry, Melitta A.
Larun, Lillebeth
Mackintosh, Kelly A.
author_facet Bianchim, Mayara S
McNarry, Melitta A.
Larun, Lillebeth
Mackintosh, Kelly A.
author_sort Bianchim, Mayara S
collection PubMed
description A growing body of research calibrating and validating accelerometers to classify physical activity intensities has led to a range of cut-points. However, the applicability of current calibration protocols to clinical populations remains to be addressed. The aim of this review was to evaluate the accuracy of the methods for calibrating and validating of accelerometers to estimate physical activity intensity thresholds for clinical populations. Six databases were searched between March and July to 2017 using text words and subject headings. Studies developing moderate-to-vigorous intensity physical activity cut-points for adult clinical populations were included. The risk of bias was assessed using the health measurement instruments and a specific checklist for calibration studies. A total of 543,741 titles were found and 323 articles were selected for full-text assessment, with 11 meeting the inclusion criteria. Twenty-three different methods for calibration were identified using different models of ActiGraph and Actical accelerometers. Disease-specific cut-points ranged from 591 to 2717 counts·min(−1) and were identified for two main groups of clinical conditions: neuromusculoskeletal disorders and metabolic diseases. The heterogeneity in the available clinical protocols hinders the applicability and comparison of the developed cut-points. As such, a mixed protocol containing a controlled laboratory exercise test and activities of daily-life is suggested. It is recommended that this be combined with a statistical approach that allows for adjustments according to disease severity or the use of machine learning models. Finally, this review highlights the generalisation of cut-points developed on healthy populations to clinical populations is inappropriate.
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spelling pubmed-69312342019-12-30 Calibration and validation of accelerometry to measure physical activity in adult clinical groups: A systematic review Bianchim, Mayara S McNarry, Melitta A. Larun, Lillebeth Mackintosh, Kelly A. Prev Med Rep Review Article A growing body of research calibrating and validating accelerometers to classify physical activity intensities has led to a range of cut-points. However, the applicability of current calibration protocols to clinical populations remains to be addressed. The aim of this review was to evaluate the accuracy of the methods for calibrating and validating of accelerometers to estimate physical activity intensity thresholds for clinical populations. Six databases were searched between March and July to 2017 using text words and subject headings. Studies developing moderate-to-vigorous intensity physical activity cut-points for adult clinical populations were included. The risk of bias was assessed using the health measurement instruments and a specific checklist for calibration studies. A total of 543,741 titles were found and 323 articles were selected for full-text assessment, with 11 meeting the inclusion criteria. Twenty-three different methods for calibration were identified using different models of ActiGraph and Actical accelerometers. Disease-specific cut-points ranged from 591 to 2717 counts·min(−1) and were identified for two main groups of clinical conditions: neuromusculoskeletal disorders and metabolic diseases. The heterogeneity in the available clinical protocols hinders the applicability and comparison of the developed cut-points. As such, a mixed protocol containing a controlled laboratory exercise test and activities of daily-life is suggested. It is recommended that this be combined with a statistical approach that allows for adjustments according to disease severity or the use of machine learning models. Finally, this review highlights the generalisation of cut-points developed on healthy populations to clinical populations is inappropriate. 2019-11-06 /pmc/articles/PMC6931234/ /pubmed/31890467 http://dx.doi.org/10.1016/j.pmedr.2019.101001 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review Article
Bianchim, Mayara S
McNarry, Melitta A.
Larun, Lillebeth
Mackintosh, Kelly A.
Calibration and validation of accelerometry to measure physical activity in adult clinical groups: A systematic review
title Calibration and validation of accelerometry to measure physical activity in adult clinical groups: A systematic review
title_full Calibration and validation of accelerometry to measure physical activity in adult clinical groups: A systematic review
title_fullStr Calibration and validation of accelerometry to measure physical activity in adult clinical groups: A systematic review
title_full_unstemmed Calibration and validation of accelerometry to measure physical activity in adult clinical groups: A systematic review
title_short Calibration and validation of accelerometry to measure physical activity in adult clinical groups: A systematic review
title_sort calibration and validation of accelerometry to measure physical activity in adult clinical groups: a systematic review
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6931234/
https://www.ncbi.nlm.nih.gov/pubmed/31890467
http://dx.doi.org/10.1016/j.pmedr.2019.101001
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