Literature DB >> 30194221

How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis of the validity of current technologies.

Ruairi O'Driscoll1, Jake Turicchi1, Kristine Beaulieu1, Sarah Scott1, Jamie Matu2, Kevin Deighton3, Graham Finlayson1, James Stubbs1.   

Abstract

OBJECTIVE: To determine the accuracy of wrist and arm-worn activity monitors' estimates of energy expenditure (EE). DATA SOURCES: SportDISCUS (EBSCOHost), PubMed, MEDLINE (Ovid), PsycINFO (EBSCOHost), Embase (Ovid) and CINAHL (EBSCOHost).
DESIGN: A random effects meta-analysis was performed to evaluate the difference in EE estimates between activity monitors and criterion measurements. Moderator analyses were conducted to determine the benefit of additional sensors and to compare the accuracy of devices used for research purposes with commercially available devices. ELIGIBILITY CRITERIA: We included studies validating EE estimates from wrist-worn or arm-worn activity monitors against criterion measures (indirect calorimetry, room calorimeters and doubly labelled water) in healthy adult populations.
RESULTS: 60 studies (104 effect sizes) were included in the meta-analysis. Devices showed variable accuracy depending on activity type. Large and significant heterogeneity was observed for many devices (I2 >75%). Combining heart rate or heat sensing technology with accelerometry decreased the error in most activity types. Research-grade devices were statistically more accurate for comparisons of total EE but less accurate than commercial devices during ambulatory activity and sedentary tasks.
CONCLUSIONS: EE estimates from wrist and arm-worn devices differ in accuracy depending on activity type. Addition of physiological sensors improves estimates of EE, and research-grade devices are superior for total EE. These data highlight the need to improve estimates of EE from wearable devices, and one way this can be achieved is with the addition of heart rate to accelerometry. PROSPEROREGISTRATION NUMBER: CRD42018085016. © Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  accelerometer; energy expenditure; meta-analysis; validation; wrist

Mesh:

Year:  2018        PMID: 30194221     DOI: 10.1136/bjsports-2018-099643

Source DB:  PubMed          Journal:  Br J Sports Med        ISSN: 0306-3674            Impact factor:   13.800


  42 in total

1.  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

2.  Ordinal Statistical Models of Physical Activity Levels from Accelerometer Data.

Authors:  Shafayet S Hossain; Drew M Lazar; Munni Begum
Journal:  Int J Exerc Sci       Date:  2021-04-01

3.  Field-based Measurement of Sleep: Agreement between Six Commercial Activity Monitors and a Validated Accelerometer.

Authors:  Andrew G Kubala; Bethany Barone Gibbs; Daniel J Buysse; Sanjay R Patel; Martica H Hall; Christopher E Kline
Journal:  Behav Sleep Med       Date:  2019-08-27       Impact factor: 2.964

4.  Perspective: Opportunities and Challenges of Technology Tools in Dietary and Activity Assessment: Bridging Stakeholder Viewpoints.

Authors:  Sai Krupa Das; Akari J Miki; Caroline M Blanchard; Edward Sazonov; Cheryl H Gilhooly; Sujit Dey; Colton B Wolk; Chor San H Khoo; James O Hill; Robin P Shook
Journal:  Adv Nutr       Date:  2022-02-01       Impact factor: 11.567

5.  Polar Vantage and Oura Physical Activity and Sleep Trackers: Validation and Comparison Study.

Authors:  André Henriksen; Frode Svartdal; Sameline Grimsgaard; Gunnar Hartvigsen; Laila Arnesdatter Hopstock
Journal:  JMIR Form Res       Date:  2022-05-27

Review 6.  Overtraining Syndrome (OTS) and Relative Energy Deficiency in Sport (RED-S): Shared Pathways, Symptoms and Complexities.

Authors:  Trent Stellingwerff; Ida A Heikura; Romain Meeusen; Stéphane Bermon; Stephen Seiler; Margo L Mountjoy; Louise M Burke
Journal:  Sports Med       Date:  2021-06-28       Impact factor: 11.136

7.  Predicting Subjective Recovery from Lower Limb Surgery Using Consumer Wearables.

Authors:  Marta Karas; Nikki Marinsek; Jörg Goldhahn; Luca Foschini; Ernesto Ramirez; Ieuan Clay
Journal:  Digit Biomark       Date:  2020-11-26

8.  Comprehensive comparison of Apple Watch and Fitbit monitors in a free-living setting.

Authors:  Yang Bai; Connie Tompkins; Nancy Gell; Dakota Dione; Tao Zhang; Wonwoo Byun
Journal:  PLoS One       Date:  2021-05-26       Impact factor: 3.240

9.  Validity of Estimating the Maximal Oxygen Consumption by Consumer Wearables: A Systematic Review with Meta-analysis and Expert Statement of the INTERLIVE Network.

Authors:  Pablo Molina-Garcia; Hannah L Notbohm; Moritz Schumann; Rob Argent; Megan Hetherington-Rauth; Julie Stang; Wilhelm Bloch; Sulin Cheng; Ulf Ekelund; Luis B Sardinha; Brian Caulfield; Jan Christian Brønd; Anders Grøntved; Francisco B Ortega
Journal:  Sports Med       Date:  2022-01-24       Impact factor: 11.928

Review 10.  Wearable activity trackers-advanced technology or advanced marketing?

Authors:  Ren-Jay Shei; Ian G Holder; Alicia S Oumsang; Brittni A Paris; Hunter L Paris
Journal:  Eur J Appl Physiol       Date:  2022-04-21       Impact factor: 3.346

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