OBJECTIVES: 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. DESIGN: Cross-sectional study. METHOD: 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. RESULTS: 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. CONCLUSIONS: 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.
OBJECTIVES: 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. DESIGN: Cross-sectional study. METHOD: 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. RESULTS: 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. CONCLUSIONS: 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.
Authors: André Henriksen; Martin Haugen Mikalsen; Ashenafi Zebene Woldaregay; Miroslav Muzny; Gunnar Hartvigsen; Laila Arnesdatter Hopstock; Sameline Grimsgaard Journal: J Med Internet Res Date: 2018-03-22 Impact factor: 5.428
Authors: Lynne M Feehan; Jasmina Geldman; Eric C Sayre; Chance Park; Allison M Ezzat; Ju Young Yoo; Clayon B Hamilton; Linda C Li Journal: JMIR Mhealth Uhealth Date: 2018-08-09 Impact factor: 4.773