Literature DB >> 16294115

Calibration of accelerometer output for children.

Patty Freedson1, David Pober, Kathleen F Janz.   

Abstract

Understanding the determinants of physical activity behavior in children and youths is essential to the design and implementation of intervention studies to increase physical activity. Objective methods to assess physical activity behavior using various types of motion detectors have been recommended as an alternative to self-report for this population because they are not subject to many of the sources of error associated with children's recall required for self-report measures. This paper reviews the calibration of four different accelerometers used most frequently to assess physical activity and sedentary behavior in children. These accelerometers are the ActiGraph, Actical, Actiwatch, and the RT3 Triaxial Research Tracker. Studies are reviewed that describe the regression modeling approaches used to calibrate these devices using directly measured energy expenditure as the criterion. Point estimates of energy expenditure or count ranges corresponding to different activity intensities from several studies are presented. For a given accelerometer, the count cut points defining the boundaries for 3 and 6 METs vary substantially among the studies reviewed even though most studies include walking, running and free-living activities in the testing protocol. Alternative data processing using the raw acceleration signal is recommended as a possible alternative approach where the actual acceleration pattern is used to characterize activity behavior. Important considerations for defining best practices for accelerometer calibration in children and youths are presented.

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Year:  2005        PMID: 16294115     DOI: 10.1249/01.mss.0000185658.28284.ba

Source DB:  PubMed          Journal:  Med Sci Sports Exerc        ISSN: 0195-9131            Impact factor:   5.411


  319 in total

1.  Use of a two-regression model for estimating energy expenditure in children.

Authors:  Scott E Crouter; Magdalene Horton; David R Bassett
Journal:  Med Sci Sports Exerc       Date:  2012-06       Impact factor: 5.411

2.  General versus central adiposity and relationship to pediatric metabolic risk.

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3.  Effect of BMI on prediction of accelerometry-based energy expenditure in youth.

Authors:  Joshua Warolin; Amanda R Carrico; Lauren E Whitaker; Li Wang; Kong Y Chen; Sari Acra; Maciej S Buchowski
Journal:  Med Sci Sports Exerc       Date:  2012-12       Impact factor: 5.411

4.  Sedentary time has a negative influence on bone mineral parameters in peripubertal boys: a 1-year prospective study.

Authors:  Artūrs Ivuškāns; Jarek Mäestu; Toivo Jürimäe; Evelin Lätt; Priit Purge; Meeli Saar; Katre Maasalu; Jaak Jürimäe
Journal:  J Bone Miner Metab       Date:  2014-02-19       Impact factor: 2.626

5.  Within-Subject Associations of Maternal Physical Activity Parenting Practices on Children's Objectively Measured Moderate-to-Vigorous Physical Activity.

Authors:  Nanette V Lopez; Chih-Hsiang Yang; Britni R Belcher; Gayla Margolin; Genevieve F Dunton
Journal:  J Pediatr Psychol       Date:  2019-04-01

6.  The effect of a physical activity intervention on bias in self-reported activity.

Authors:  Daniel R Taber; June Stevens; David M Murray; John P Elder; Larry S Webber; Jared B Jobe; Leslie A Lytle
Journal:  Ann Epidemiol       Date:  2009-02-20       Impact factor: 3.797

7.  Toward a Better Understanding of the Link Between Parent and Child Physical Activity Levels: The Moderating Role of Parental Encouragement.

Authors:  Eleanor B Tate; Anuja Shah; Malia Jones; Mary Ann Pentz; Yue Liao; Genevieve Dunton
Journal:  J Phys Act Health       Date:  2014-12-10

8.  Neighborhood park use by children: use of accelerometry and global positioning systems.

Authors:  Genevieve Fridlund Dunton; Estela Almanza; Michael Jerrett; Jennifer Wolch; Mary Ann Pentz
Journal:  Am J Prev Med       Date:  2014-02       Impact factor: 5.043

9.  Reduced cardiorespiratory fitness, low physical activity and an urban environment are independently associated with increased cardiovascular risk in children.

Authors:  S Kriemler; S Manser-Wenger; L Zahner; C Braun-Fahrländer; C Schindler; J J Puder
Journal:  Diabetologia       Date:  2008-06-17       Impact factor: 10.122

10.  Construct validity of selected measures of physical activity beliefs and motives in fifth and sixth grade boys and girls.

Authors:  Rod K Dishman; Ruth P Saunders; Kerry L McIver; Marsha Dowda; Russell R Pate
Journal:  J Pediatr Psychol       Date:  2013-03-04
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