Literature DB >> 22971560

Comparison of epoch and uniaxial versus triaxial accelerometers in the measurement of physical activity in preschool children: a validation study.

Jane F Hislop1, Cathy Bulley, Tom H Mercer, John J Reilly.   

Abstract

The objectives of this study were to explore whether triaxial is more accurate than uniaxial accelerometry and whether shorter sampling periods (epochs) are more accurate than longer epochs. Physical activity data from uniaxial and triaxial (RT3) devices were collected in 1-s epochs from 31 preschool children (15 males, 16 females, 4.4 ± 0.8 yrs) who were videoed while they engaged in 1-hr of free-play. Video data were coded using the Children's Activity Rating Scale (CARS). A significant difference (p < .001) in the number of minutes classified as moderate to vigorous physical activity (MVPA) was found between the RT3 and the CARS (p < .002) using the cut point of relaxed walk. No significant difference was found between the GT1M and the CARS or between the RT3 and the CARS using the cut point for light jog. Shorter epochs resulted in significantly greater overestimation of MVPA, with the bias increasing from 0.7 mins at 15-s to 3.2 mins at 60-s epochs for the GT1M and 0 mins to 1.7 mins for the RT3. Results suggest that there was no advantage of a triaxial accelerometer over a uniaxial model. Shorter epochs result in significantly higher number of minutes of MVPA with smaller bias relative to direct observation.

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Year:  2012        PMID: 22971560     DOI: 10.1123/pes.24.3.450

Source DB:  PubMed          Journal:  Pediatr Exerc Sci        ISSN: 0899-8493            Impact factor:   2.333


  11 in total

1.  Assessment of 24-hour physical behaviour in children and adolescents via wearables: a systematic review of free-living validation studies.

Authors:  Marco Giurgiu; Simon Kolb; Carina Nigg; Alexander Burchartz; Irina Timm; Marlissa Becker; Ellen Rulf; Ann-Kathrin Doster; Elena Koch; Johannes B J Bussmann; Claudio Nigg; Ulrich W Ebner-Priemer; Alexander Woll
Journal:  BMJ Open Sport Exerc Med       Date:  2022-05-12

2.  Using hidden markov models to improve quantifying physical activity in accelerometer data - a simulation study.

Authors:  Vitali Witowski; Ronja Foraita; Yannis Pitsiladis; Iris Pigeot; Norman Wirsik
Journal:  PLoS One       Date:  2014-12-02       Impact factor: 3.240

3.  Toddler physical activity study: laboratory and community studies to evaluate accelerometer validity and correlates.

Authors:  Erin R Hager; Candice E Gormley; Laura W Latta; Margarita S Treuth; Laura E Caulfield; Maureen M Black
Journal:  BMC Public Health       Date:  2016-09-06       Impact factor: 3.295

4.  Effect of Physical Activity on Cognitive Development: Protocol for a 15-Year Longitudinal Follow-Up Study.

Authors:  Guanggao Zhao; Minghui Quan; Liqiang Su; Hanbin Zhang; Jiayi Zhang; Jinming Zhang; Hui Fang; Zhen-Bo Cao; Zheng Zhu; Zhanbin Niu; Ru Wang; Peijie Chen
Journal:  Biomed Res Int       Date:  2017-09-28       Impact factor: 3.411

5.  Are preschool children active enough in Shanghai: an accelerometer-based cross-sectional study.

Authors:  Minghui Quan; Hanbin Zhang; Jiayi Zhang; Tang Zhou; Jinming Zhang; Guanggao Zhao; Hui Fang; Shunli Sun; Ru Wang; Peijie Chen
Journal:  BMJ Open       Date:  2019-04-25       Impact factor: 2.692

6.  Associations between Daily Step Counts and Physical Fitness in Preschool Children.

Authors:  Chunyi Fang; Jinming Zhang; Tang Zhou; Longkai Li; Yaofei Lu; Zan Gao; Minghui Quan
Journal:  J Clin Med       Date:  2020-01-07       Impact factor: 4.241

Review 7.  Systematic review of accelerometer-based methods for 24-h physical behavior assessment in young children (0-5 years old).

Authors:  Annelinde Lettink; Teatske M Altenburg; Jelle Arts; Vincent T van Hees; Mai J M Chinapaw
Journal:  Int J Behav Nutr Phys Act       Date:  2022-09-08       Impact factor: 8.915

8.  Accelerometric estimates of physical activity vary unstably with data handling.

Authors:  Maia P Smith; Marie Standl; Joachim Heinrich; Holger Schulz
Journal:  PLoS One       Date:  2017-11-06       Impact factor: 3.240

9.  Uni- and triaxial accelerometric signals agree during daily routine, but show differences between sports.

Authors:  Maia P Smith; Alexander Horsch; Marie Standl; Joachim Heinrich; Holger Schulz
Journal:  Sci Rep       Date:  2018-10-10       Impact factor: 4.379

10.  Machine Learning Models for Classifying Physical Activity in Free-Living Preschool Children.

Authors:  Matthew N Ahmadi; Toby G Pavey; Stewart G Trost
Journal:  Sensors (Basel)       Date:  2020-08-05       Impact factor: 3.576

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