Literature DB >> 31269409

Use of consumer monitors for estimating energy expenditure in youth.

Samuel R LaMunion1, Andrew L Blythe1, Paul R Hibbing1, Andrew S Kaplan2, Brandon J Clendenin1, Scott E Crouter1.   

Abstract

The purpose of this study was to compare energy expenditure (EE) estimates from 5 consumer physical activity monitors (PAMs) to indirect calorimetry in a sample of youth. Eighty-nine youth (mean (SD); age, 12.3 (3.4) years; 50% female) performed 16 semi-structured activities. Activities were performed in duplicate across 2 visits. Participants wore a Cosmed K4b2 (criterion for EE), an Apple Watch 2 (left wrist), Mymo Tracker (right hip), and Misfit Shine 2 devices (right hip; right shoe). Participants were randomized to wear a Samsung Gear Fit 2 or a Fitbit Charge 2 on the right wrist. Oxygen consumption was converted to EE by subtracting estimated basal EE (Schofield's equation) from the measured gross EE. EE from each visit was summed across the 2 visit days for comparison with the total EE recorded from the PAMs. All consumer PAMs estimated gross EE, except for the Apple Watch 2 (net Active EE). Paired t tests were used to assess differences between estimated (PAM) and measured (K4b2) EE. Mean absolute percent error (MAPE) was used to assess individual-level error. The Mymo Tracker was not significantly different from measured EE and was within 15.9 kcal of measured kilocalories (p = 0.764). Mean percent errors ranged from 3.5% (Mymo Tracker) to 48.2% (Apple Watch 2). MAPE ranged from 16.8% (Misfit Shine 2 - right hip) to 49.9% (Mymo Tracker). Novelty Only the Mymo Tracker was not significantly different from measured EE but had the greatest individual error. The Misfit Shine 2 - right hip had the lowest individual error. Caution is warranted when using consumer PAMs in youth for tracking EE.

Entities:  

Keywords:  Apple Watch; Fitbit; activity tracker; activité physique; dispositifs portables; fitness tracker; indicateur d’activité; moniteur d’activité physique; physical activity; wearable devices

Year:  2019        PMID: 31269409      PMCID: PMC7251475          DOI: 10.1139/apnm-2019-0129

Source DB:  PubMed          Journal:  Appl Physiol Nutr Metab        ISSN: 1715-5312            Impact factor:   2.665


  22 in total

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2.  Validity of consumer-based physical activity monitors.

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3.  Predicting basal metabolic rate, new standards and review of previous work.

Authors:  W N Schofield
Journal:  Hum Nutr Clin Nutr       Date:  1985

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Journal:  Healthc Inform Res       Date:  2015-10-31

5.  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

6.  Exploring Metrics to Express Energy Expenditure of Physical Activity in Youth.

Authors:  Robert G McMurray; Nancy F Butte; Scott E Crouter; Stewart G Trost; Karin A Pfeiffer; David R Bassett; Maurice R Puyau; David Berrigan; Kathleen B Watson; Janet E Fulton
Journal:  PLoS One       Date:  2015-06-23       Impact factor: 3.240

7.  A Bit of Fit: Minimalist Intervention in Adolescents Based on a Physical Activity Tracker.

Authors:  Jeffrey Gaudet; François Gallant; Mathieu Bélanger
Journal:  JMIR Mhealth Uhealth       Date:  2017-07-06       Impact factor: 4.773

8.  Assessment of laboratory and daily energy expenditure estimates from consumer multi-sensor physical activity monitors.

Authors:  Enhad A Chowdhury; Max J Western; Thomas E Nightingale; Oliver J Peacock; Dylan Thompson
Journal:  PLoS One       Date:  2017-02-24       Impact factor: 3.240

9.  Comparison of Consumer and Research Monitors under Semistructured Settings.

Authors:  Yang Bai; Gregory J Welk; Yoon Ho Nam; Joey A Lee; Jung-Min Lee; Youngwon Kim; Nathan F Meier; Philip M Dixon
Journal:  Med Sci Sports Exerc       Date:  2016-01       Impact factor: 5.411

10.  Youth Oriented Activity Trackers: Comprehensive Laboratory- and Field-Based Validation.

Authors:  John R Sirard; Brittany Masteller; Patty S Freedson; Albert Mendoza; Amanda Hickey
Journal:  J Med Internet Res       Date:  2017-07-19       Impact factor: 5.428

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  3 in total

1.  Are Wrist-Worn Activity Trackers and Mobile Applications Valid for Assessing Physical Activity in High School Students? Wearfit Study.

Authors:  Jesús Viciana; Carolina Casado-Robles; Santiago Guijarro-Romero; Daniel Mayorga-Vega
Journal:  J Sports Sci Med       Date:  2022-09-01       Impact factor: 4.017

2.  Youth Metabolic Equivalents Differ Depending on Operational Definitions.

Authors:  Paul R Hibbing; David R Bassett; Dawn P Coe; Samuel R Lamunion; Scott E Crouter
Journal:  Med Sci Sports Exerc       Date:  2020-08

3.  Evaluating the Performance of Sensor-based Bout Detection Algorithms: The Transition Pairing Method.

Authors:  Paul R Hibbing; Samuel R LaMunion; Haileab Hilafu; Scott E Crouter
Journal:  J Meas Phys Behav       Date:  2020-05-20
  3 in total

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