Literature DB >> 10993419

A comparative evaluation of three accelerometry-based physical activity monitors.

G J Welk1, S N Blair, K Wood, S Jones, R W Thompson.   

Abstract

PURPOSE: Accelerometry-based activity monitors offer promise for the assessment of free-living physical activity. They provide an objective record of frequency, intensity, and duration of physical activity with minimal burden on participants. The purpose of this study was to evaluate the absolute and relative validity of three contemporary activity monitors (Computer Science and Applications, Inc. [CSA], Tritrac, and Biotrainer) under both laboratory and field conditions.
METHODS: Fifty-two participants completed two 30-min choreographed routines designed to simulate a variety of lifestyle physical activities. Three different treadmill paces were completed in both routines to evaluate reliability and validity under laboratory conditions. Six different lifestyle activities were also examined to evaluate the validity of the monitors under field conditions. During each routine, the activity levels of participants were monitored with the three activity monitors as well as by indirect calorimetry systems.
RESULTS: The correlations between the monitors and measured VO2 were higher for treadmill activity (mean r = 0.86) compared with lifestyle activity (mean r = 0.55). Correlations among the different monitors were high for both treadmill (r = 0.86) and lifestyle activities (r = 0.70), suggesting that the monitors provide similar information under both conditions. Under laboratory conditions, the CSA yielded accurate predictions of energy expenditure (EE), whereas the Tritrac and Biotrainer tended to overestimate the EE (101-136% of measured value). The Tritrac, however, was found to have less error in individual estimates of EE. Under field conditions, all of the monitors underestimated EE (range: 42-67% of measured value).
CONCLUSION: The observed differences among the monitors were attributed primarily to differences in the accuracy of the calibration equations rather than to the monitors themselves. Further research is needed to better understand how to use these devices for field-based assessments of physical activity.

Entities:  

Mesh:

Year:  2000        PMID: 10993419     DOI: 10.1097/00005768-200009001-00008

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


  76 in total

1.  Validity of uniaxial accelerometry during activities of daily living in children.

Authors:  Joey C Eisenmann; Scott J Strath; Danny Shadrick; Paul Rigsby; Nicole Hirsch; Leigh Jacobson
Journal:  Eur J Appl Physiol       Date:  2003-10-21       Impact factor: 3.078

2.  Measurement and prediction of METs during household activities in 35- to 45-year-old females.

Authors:  Anthony G Brooks; Robert T Withers; Christopher J Gore; Andrew J Vogler; John Plummer; John Cormack
Journal:  Eur J Appl Physiol       Date:  2003-12-18       Impact factor: 3.078

3.  Predicting energy expenditure of physical activity using hip- and wrist-worn accelerometers.

Authors:  Kong Y Chen; Sari A Acra; Karen Majchrzak; Candice L Donahue; Lemont Baker; Linda Clemens; Ming Sun; Maciej S Buchowski
Journal:  Diabetes Technol Ther       Date:  2003       Impact factor: 6.118

4.  Defining accelerometer thresholds for activity intensities in adolescent girls.

Authors:  Margarita S Treuth; Kathryn Schmitz; Diane J Catellier; Robert G McMurray; David M Murray; M Joao Almeida; Scott Going; James E Norman; Russell Pate
Journal:  Med Sci Sports Exerc       Date:  2004-07       Impact factor: 5.411

Review 5.  Physical activity questionnaires for youth: a systematic review of measurement properties.

Authors:  Mai J M Chinapaw; Lidwine B Mokkink; Mireille N M van Poppel; Willem van Mechelen; Caroline B Terwee
Journal:  Sports Med       Date:  2010-07-01       Impact factor: 11.136

6.  Characteristics of walking, activity, fear of falling, and falls in community-dwelling older adults by residence.

Authors:  David M Wert; Jaime B Talkowski; Jennifer Brach; Jessie VanSwearingen
Journal:  J Geriatr Phys Ther       Date:  2010 Jan-Mar       Impact factor: 3.381

7.  Predicting energy expenditure from accelerometry counts in adolescent girls.

Authors:  Kathryn H Schmitz; Margarita Treuth; Peter Hannan; Robert McMurray; Kimberly B Ring; Diane Catellier; Russ Pate
Journal:  Med Sci Sports Exerc       Date:  2005-01       Impact factor: 5.411

8.  The effect of social desirability and social approval on self-reports of physical activity.

Authors:  Swann Arp Adams; Charles E Matthews; Cara B Ebbeling; Charity G Moore; Joan E Cunningham; Jeanette Fulton; James R Hebert
Journal:  Am J Epidemiol       Date:  2005-02-15       Impact factor: 4.897

9.  Cardiovascular health in adults with type 1 diabetes.

Authors:  Margaret M McCarthy; Marjorie Funk; Margaret Grey
Journal:  Prev Med       Date:  2016-08-12       Impact factor: 4.018

10.  Accuracy of optimized branched algorithms to assess activity-specific physical activity energy expenditure.

Authors:  Andy G Edwards; James O Hill; William C Byrnes; Raymond C Browning
Journal:  Med Sci Sports Exerc       Date:  2010-04       Impact factor: 5.411

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.