Literature DB >> 20142781

Accelerometer output and MET values of common physical activities.

Sarah L Kozey1, Kate Lyden, Cheryl A Howe, John W Staudenmayer, Patty S Freedson.   

Abstract

PURPOSE: This article 1) provides the calibration procedures and methods for metabolic and activity monitor data collection, 2) compares measured MET values to the MET values from the compendium of physical activities, and 3) examines the relationship between accelerometer output and METs for a range of physical activities.
METHODS: Participants (N = 277) completed 11 activities for 7 min each from a menu of 23 physical activities. Oxygen consumption (V O2) was measured using a portable metabolic system, and an accelerometer was worn. MET values were defined as measured METs (V O2/measured resting metabolic rate) and standard METs (V O2/3.5 mL.kg.min). For the total sample and by subgroup (age [young < 40 yr], sex, and body mass index [normal weight < 25 kg.m]), measured METs and standard METs were compared with the compendium, using 95% confidence intervals to determine statistical significance (alpha = 0.05). Average counts per minute for each activity and the linear association between counts per minute and METs are presented.
RESULTS: Compendium METs were different than measured METs for 17/21 activities (81%). The number of activities different than the compendium was similar between subgroups or when standard METs were used. The average counts for the activities ranged from 11 counts per minute (dishes) to 7490 counts per minute (treadmill: 2.23 m.s, 3%). The r between counts and METs was 0.65.
CONCLUSIONS: This study provides valuable information about data collection, metabolic responses, and accelerometer output for common physical activities in a diverse participant sample. The compendium should be updated with additional empirical data, and linear regression models are inappropriate for accurately predicting METs from accelerometer output.

Entities:  

Mesh:

Year:  2010        PMID: 20142781      PMCID: PMC2924952          DOI: 10.1249/MSS.0b013e3181d479f2

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


  33 in total

1.  Validity of accelerometry for the assessment of moderate intensity physical activity in the field.

Authors:  D Hendelman; K Miller; C Baggett; E Debold; P Freedson
Journal:  Med Sci Sports Exerc       Date:  2000-09       Impact factor: 5.411

Review 2.  Performance characteristics of gas analysis systems: what we know and what we need to know.

Authors:  G Atkinson; R C R Davison; A M Nevill
Journal:  Int J Sports Med       Date:  2005-02       Impact factor: 3.118

3.  The energy cost of household and garden activities in 55- to 65-year-old males.

Authors:  Simon M Gunn; Anthony G Brooks; Robert T Withers; Christopher J Gore; John L Plummer; John Cormack
Journal:  Eur J Appl Physiol       Date:  2005-04-07       Impact factor: 3.078

4.  Self-selected exercise intensity during household/garden activities and walking in 55 to 65-year-old females.

Authors:  Robert T Withers; Anthony G Brooks; Simon M Gunn; John L Plummer; Christopher J Gore; John Cormack
Journal:  Eur J Appl Physiol       Date:  2006-06-10       Impact factor: 3.078

Review 5.  Best practice methods to apply to measurement of resting metabolic rate in adults: a systematic review.

Authors:  Charlene Compher; David Frankenfield; Nancy Keim; Lori Roth-Yousey
Journal:  J Am Diet Assoc       Date:  2006-06

6.  Development of novel techniques to classify physical activity mode using accelerometers.

Authors:  David M Pober; John Staudenmayer; Christopher Raphael; Patty S Freedson
Journal:  Med Sci Sports Exerc       Date:  2006-09       Impact factor: 5.411

7.  Improving assessment of daily energy expenditure by identifying types of physical activity with a single accelerometer.

Authors:  A G Bonomi; G Plasqui; A H C Goris; K R Westerterp
Journal:  J Appl Physiol (1985)       Date:  2009-06-25

8.  Validity of four motion sensors in measuring moderate intensity physical activity.

Authors:  D R Bassett; B E Ainsworth; A M Swartz; S J Strath; W L O'Brien; G A King
Journal:  Med Sci Sports Exerc       Date:  2000-09       Impact factor: 5.411

9.  Physical activity in the United States measured by accelerometer.

Authors:  Richard P Troiano; David Berrigan; Kevin W Dodd; Louise C Mâsse; Timothy Tilert; Margaret McDowell
Journal:  Med Sci Sports Exerc       Date:  2008-01       Impact factor: 5.411

Review 10.  Accelerometers and pedometers: methodology and clinical application.

Authors:  Kirsten Corder; Søren Brage; Ulf Ekelund
Journal:  Curr Opin Clin Nutr Metab Care       Date:  2007-09       Impact factor: 4.294

View more
  41 in total

1.  Body metabolic rate and electromyographic activities of antigravitational muscles in supine and standing postures.

Authors:  Alessandro Rubini; Antonio Paoli; Andrea Parmagnani
Journal:  Eur J Appl Physiol       Date:  2011-09-27       Impact factor: 3.078

2.  Higher Precision of Heart Rate Compared with VO2 to Predict Exercise Intensity in Endurance-Trained Runners.

Authors:  Victor M Reis; Roland Van den Tillaar; Mario C Marques
Journal:  J Sports Sci Med       Date:  2011-03-01       Impact factor: 2.988

3.  Evaluation of artificial neural network algorithms for predicting METs and activity type from accelerometer data: validation on an independent sample.

Authors:  Patty S Freedson; Kate Lyden; Sarah Kozey-Keadle; John Staudenmayer
Journal:  J Appl Physiol (1985)       Date:  2011-09-01

4.  METs and accelerometry of walking in older adults: standard versus measured energy cost.

Authors:  Katherine S Hall; Cheryl A Howe; Sharon R Rana; Clara L Martin; Miriam C Morey
Journal:  Med Sci Sports Exerc       Date:  2013-03       Impact factor: 5.411

5.  Energy cost of common activities in children and adolescents.

Authors:  Kate Lyden; Sarah Kozey Keadle; John Staudenmayer; Patty Freedson; Sofiya Alhassan
Journal:  J Phys Act Health       Date:  2012-02-29

Review 6.  Computational methods for estimating energy expenditure in human physical activities.

Authors:  Shaopeng Liu; Robert X Gao; Patty S Freedson
Journal:  Med Sci Sports Exerc       Date:  2012-11       Impact factor: 5.411

7.  Validation study of Polar V800 accelerometer.

Authors:  Adrián Hernández-Vicente; Alejandro Santos-Lozano; Katrien De Cocker; Nuria Garatachea
Journal:  Ann Transl Med       Date:  2016-08

8.  The Stanford Leisure-Time Activity Categorical Item (L-Cat): a single categorical item sensitive to physical activity changes in overweight/obese women.

Authors:  M Kiernan; D E Schoffman; K Lee; S D Brown; J M Fair; M G Perri; W L Haskell
Journal:  Int J Obes (Lond)       Date:  2013-04-16       Impact factor: 5.095

9.  Gross and relative energy cost of domestic household activities in Asian men.

Authors:  H-J Goh; P Govindharajulu; S G Camps; S-Y Tan; C J Henry
Journal:  Eur J Clin Nutr       Date:  2016-07-27       Impact factor: 4.016

10.  A method to estimate free-living active and sedentary behavior from an accelerometer.

Authors:  Kate Lyden; Sarah Kozey Keadle; John Staudenmayer; Patty S Freedson
Journal:  Med Sci Sports Exerc       Date:  2014-02       Impact factor: 5.411

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.