Literature DB >> 26154336

Comparison of Consumer and Research Monitors under Semistructured Settings.

Yang Bai1, Gregory J Welk, Yoon Ho Nam, Joey A Lee, Jung-Min Lee, Youngwon Kim, Nathan F Meier, Philip M Dixon.   

Abstract

PURPOSE: This study evaluated the relative validity of different consumer and research activity monitors during semistructured periods of sedentary activity, aerobic exercise, and resistance exercise.
METHODS: Fifty-two (28 male and 24 female) participants age 18-65 yr performed 20 min of self-selected sedentary activity, 25 min of aerobic exercise, and 25 min of resistance exercise, with 5 min of rest between each activity. Each participant wore five wrist-worn consumer monitors [Fitbit Flex, Jawbone Up24, Misfit Shine (MS), Nike+ Fuelband SE (NFS), and Polar Loop] and two research monitors [ActiGraph GT3X+ on the waist and BodyMedia Core (BMC) on the arm] while being concurrently monitored with Oxycon Mobile (OM), a portable metabolic measuring system. Energy expenditure (EE) on different activity sessions was measured by OM and estimated by all monitors.
RESULTS: Mean absolute percent error (MAPE) values for the full 80-min protocol ranged from 15.3% (BMC) to 30.4% (MS). EE estimates from ActiGraph GT3X+ were found to be equivalent to those from OM (± 10% equivalence zone, 285.1-348.5). Correlations between OM and the various monitors were generally high (ranged between 0.71 and 0.90). Three monitors had MAPE values lower than 20% for sedentary activity: BMC (15.7%), MS (18.2%), and NFS (20.0%). Two monitors had MAPE values lower than 20% for aerobic exercise: BMC (17.2%) and NFS (18.5%). None of the monitors had MAPE values lower than 25% for resistance exercise.
CONCLUSION: Overall, the research monitors and Fitbit Flex, Jawbone Up24, and NFS provided reasonably accurate total EE estimates at the individual level. However, larger error was evident for individual activities, especially resistance exercise. Further research is needed to examine these monitors across various activities and intensities as well as under real-world conditions.

Entities:  

Mesh:

Year:  2016        PMID: 26154336     DOI: 10.1249/MSS.0000000000000727

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


  53 in total

1.  Validation of a Self-Monitoring Tool for Use in Exercise Therapy.

Authors:  Camilla S Powierza; Michael D Clark; Jaime M Hughes; Kevin A Carneiro; Jason P Mihalik
Journal:  PM R       Date:  2017-04-09       Impact factor: 2.298

2.  Use of consumer monitors for estimating energy expenditure in youth.

Authors:  Samuel R LaMunion; Andrew L Blythe; Paul R Hibbing; Andrew S Kaplan; Brandon J Clendenin; Scott E Crouter
Journal:  Appl Physiol Nutr Metab       Date:  2019-07-03       Impact factor: 2.665

3.  Investigating the within-person relationships between activity levels and sleep duration using Fitbit data.

Authors:  Yue Liao; Michael C Robertson; Andrea Winne; Ivan H C Wu; Thuan A Le; Diwakar D Balachandran; Karen M Basen-Engquist
Journal:  Transl Behav Med       Date:  2021-03-16       Impact factor: 3.046

4.  Feasibility of a telephone and web-based physical activity intervention for women shift workers.

Authors:  S E Neil-Sztramko; C C Gotay; C M Sabiston; P A Demers; K C Campbell
Journal:  Transl Behav Med       Date:  2017-06       Impact factor: 3.046

Review 5.  How consumer physical activity monitors could transform human physiology research.

Authors:  Stephen P Wright; Tyish S Hall Brown; Scott R Collier; Kathryn Sandberg
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2017-01-04       Impact factor: 3.619

6.  A Primer on the Use of Equivalence Testing for Evaluating Measurement Agreement.

Authors:  Philip M Dixon; Pedro F Saint-Maurice; Youngwon Kim; Paul Hibbing; Yang Bai; Gregory J Welk
Journal:  Med Sci Sports Exerc       Date:  2018-04       Impact factor: 5.411

Review 7.  The Wild Wild West: A Framework to Integrate mHealth Software Applications and Wearables to Support Physical Activity Assessment, Counseling and Interventions for Cardiovascular Disease Risk Reduction.

Authors:  Felipe Lobelo; Heval M Kelli; Sheri Chernetsky Tejedor; Michael Pratt; Michael V McConnell; Seth S Martin; Gregory J Welk
Journal:  Prog Cardiovasc Dis       Date:  2016-02-26       Impact factor: 8.194

8.  Validation of a method for estimating energy expenditure during walking in middle-aged adults.

Authors:  Nathan Caron; Teddy Caderby; Nicolas Peyrot; Chantal Verkindt; Georges Dalleau
Journal:  Eur J Appl Physiol       Date:  2017-12-09       Impact factor: 3.078

9.  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

10.  Wearable Devices and Smartphones for Activity Tracking Among People with Serious Mental Illness.

Authors:  John A Naslund; Kelly A Aschbrenner; Stephen J Bartels
Journal:  Ment Health Phys Act       Date:  2016-03
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