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Validation of the Fitbit One, Garmin Vivofit and Jawbone UP activity tracker in estimation of energy expenditure during treadmill walking and running

Overview of attention for article published in Journal of Medical Engineering & Technology, December 2016
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Title
Validation of the Fitbit One, Garmin Vivofit and Jawbone UP activity tracker in estimation of energy expenditure during treadmill walking and running
Published in
Journal of Medical Engineering & Technology, December 2016
DOI 10.1080/03091902.2016.1253795
Pubmed ID
Authors

Kym Price, Stephen R. Bird, Noel Lythgo, Isaac S. Raj, Jason Y. L. Wong, Chris Lynch

Abstract

To determine the validity of energy expenditure estimation made by the Fitbit One, Garmin Vivofit and Jawbone UP activity trackers during treadmill walking and running. Determining validity of such trackers will inform the interpretation of the data they generate. Cross-sectional study. Fourteen adults walked at 0.70, 1.25, 1.80 ms(-1) and ran at 2.22, 2.78, 3.33 ms(-1) on a treadmill wearing a Fitbit One, Garmin Vivofit and Jawbone UP. Estimation of energy expenditure from each tracker was compared to measurement from indirect calorimetry (criterion). Paired t-tests, correlation coefficients and Bland-Altman plots assessed agreement and proportional bias. Mean percentage difference assessed magnitude of difference between estimated and criterion energy expenditure for each speed. Energy expenditure estimates from the Fitbit One and Garmin Vivofit correlated significantly (p< 0.01; r= 0.702; 0.854) with criterion across all gait speeds (0.70-3.33 ms(-1)). Fitbit One, Garmin Vivofit and Jawbone UP correlated significantly (p < 0.05; r = 0.729; 0.711; 0.591) with criterion across all walking speeds (0.70-1.80 ms(-)(1)). However, only the Garmin Vivofit correlated significantly (p< 0.05; r = 0.346) with energy expenditure estimations from criterion across running speeds (2.22-3.33 ms(-)(1)). Bland-Altman plots showed proportional bias for the Fitbit One and Garmin Vivofit. Energy expenditure estimations of single speeds were overestimated by the Fitbit One and underestimated by the Garmin Vivofit. Energy expenditure reported by the devices distinguished between walking and running, with a general increase as exercise intensity increased. However, the reported energy expenditure from these devices should be interpreted with caution, given their potential bias and error. Practical implications Although devices report the same outcome of EE estimation, they are not equivalent to each other and differ from criterion measurements during walking and running. These devices are not suitable as research measurement tools for recording precise and accurate EE estimates but may be suitable for use in interventions of behaviour change as they provide feedback to user on trends in energy expenditure. If intending to use these devices in studies where precise measurements of energy expenditure are required, researchers need to undertake specific validation and reliability studies prior to interventions and the collection of cross-sectional data.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 178 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Finland 1 <1%
Netherlands 1 <1%
Germany 1 <1%
Unknown 175 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 16%
Student > Master 28 16%
Student > Bachelor 22 12%
Researcher 20 11%
Student > Postgraduate 10 6%
Other 34 19%
Unknown 35 20%
Readers by discipline Count As %
Sports and Recreations 34 19%
Medicine and Dentistry 26 15%
Computer Science 13 7%
Nursing and Health Professions 12 7%
Engineering 11 6%
Other 40 22%
Unknown 42 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 June 2017.
All research outputs
#15,565,752
of 25,119,447 outputs
Outputs from Journal of Medical Engineering & Technology
#292
of 399 outputs
Outputs of similar age
#232,430
of 427,954 outputs
Outputs of similar age from Journal of Medical Engineering & Technology
#3
of 3 outputs
Altmetric has tracked 25,119,447 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 399 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 427,954 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.