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Sedentary Behaviour Profiling of Office Workers: A Sensitivity Analysis of Sedentary Cut-Points
Measuring sedentary behaviour and physical activity with wearable sensors provides detailed information on activity patterns and can serve health interventions. At the basis of activity analysis stands the ability to distinguish sedentary from active time. As there is no consensus regarding the opti...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4732055/ https://www.ncbi.nlm.nih.gov/pubmed/26712758 http://dx.doi.org/10.3390/s16010022 |
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author | Boerema, Simone T. Essink, Gerard B. Tönis, Thijs M. van Velsen, Lex Hermens, Hermie J. |
author_facet | Boerema, Simone T. Essink, Gerard B. Tönis, Thijs M. van Velsen, Lex Hermens, Hermie J. |
author_sort | Boerema, Simone T. |
collection | PubMed |
description | Measuring sedentary behaviour and physical activity with wearable sensors provides detailed information on activity patterns and can serve health interventions. At the basis of activity analysis stands the ability to distinguish sedentary from active time. As there is no consensus regarding the optimal cut-point for classifying sedentary behaviour, we studied the consequences of using different cut-points for this type of analysis. We conducted a battery of sitting and walking activities with 14 office workers, wearing the Promove 3D activity sensor to determine the optimal cut-point (in counts per minute (m·s(−2))) for classifying sedentary behaviour. Then, 27 office workers wore the sensor for five days. We evaluated the sensitivity of five sedentary pattern measures for various sedentary cut-points and found an optimal cut-point for sedentary behaviour of 1660 × 10(−3) m·s(−2). Total sedentary time was not sensitive to cut-point changes within ±10% of this optimal cut-point; other sedentary pattern measures were not sensitive to changes within the ±20% interval. The results from studies analyzing sedentary patterns, using different cut-points, can be compared within these boundaries. Furthermore, commercial, hip-worn activity trackers can implement feedback and interventions on sedentary behaviour patterns, using these cut-points. |
format | Online Article Text |
id | pubmed-4732055 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-47320552016-02-12 Sedentary Behaviour Profiling of Office Workers: A Sensitivity Analysis of Sedentary Cut-Points Boerema, Simone T. Essink, Gerard B. Tönis, Thijs M. van Velsen, Lex Hermens, Hermie J. Sensors (Basel) Article Measuring sedentary behaviour and physical activity with wearable sensors provides detailed information on activity patterns and can serve health interventions. At the basis of activity analysis stands the ability to distinguish sedentary from active time. As there is no consensus regarding the optimal cut-point for classifying sedentary behaviour, we studied the consequences of using different cut-points for this type of analysis. We conducted a battery of sitting and walking activities with 14 office workers, wearing the Promove 3D activity sensor to determine the optimal cut-point (in counts per minute (m·s(−2))) for classifying sedentary behaviour. Then, 27 office workers wore the sensor for five days. We evaluated the sensitivity of five sedentary pattern measures for various sedentary cut-points and found an optimal cut-point for sedentary behaviour of 1660 × 10(−3) m·s(−2). Total sedentary time was not sensitive to cut-point changes within ±10% of this optimal cut-point; other sedentary pattern measures were not sensitive to changes within the ±20% interval. The results from studies analyzing sedentary patterns, using different cut-points, can be compared within these boundaries. Furthermore, commercial, hip-worn activity trackers can implement feedback and interventions on sedentary behaviour patterns, using these cut-points. MDPI 2015-12-25 /pmc/articles/PMC4732055/ /pubmed/26712758 http://dx.doi.org/10.3390/s16010022 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Boerema, Simone T. Essink, Gerard B. Tönis, Thijs M. van Velsen, Lex Hermens, Hermie J. Sedentary Behaviour Profiling of Office Workers: A Sensitivity Analysis of Sedentary Cut-Points |
title | Sedentary Behaviour Profiling of Office Workers: A Sensitivity Analysis of Sedentary Cut-Points |
title_full | Sedentary Behaviour Profiling of Office Workers: A Sensitivity Analysis of Sedentary Cut-Points |
title_fullStr | Sedentary Behaviour Profiling of Office Workers: A Sensitivity Analysis of Sedentary Cut-Points |
title_full_unstemmed | Sedentary Behaviour Profiling of Office Workers: A Sensitivity Analysis of Sedentary Cut-Points |
title_short | Sedentary Behaviour Profiling of Office Workers: A Sensitivity Analysis of Sedentary Cut-Points |
title_sort | sedentary behaviour profiling of office workers: a sensitivity analysis of sedentary cut-points |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4732055/ https://www.ncbi.nlm.nih.gov/pubmed/26712758 http://dx.doi.org/10.3390/s16010022 |
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