Validation of the Mywellness Key in Walking and Running Speeds
Marco Bergamin1,, Andrea Ermolao1, John C. Sieverdes2, Marco Zaccaria1, Silvano Zanuso3
Author Information
1 Sports Medicine Division, Department of Medical and Surgical Sciences, University of Padova, Padova, Italy,
2 Arnold School of Public Health, Department of Exercise Science, University of South Carolina, Columbia, USA
3 Centre for Sport Sciences and Human Performance, Department of Sports Science, University of Greenwich, London, UK
Marco Bergamin ✉ Sports Medicine Division, Department of Medical and Surgical Sciences, University of Padova, Padova, Italy Email: marco.bergamin@unipd.it
Publish Date
Received: 14-09-2011 Accepted: 24-11-2011 Published (online): 01-03-2012
Marco Bergamin, Andrea Ermolao, John C. Sieverdes, Marco Zaccaria, Silvano Zanuso. (2012) Validation of the Mywellness Key in Walking and Running Speeds. Journal of Sports Science and Medicine(11), 57 - 63.
Marco Bergamin, Andrea Ermolao, John C. Sieverdes, Marco Zaccaria, Silvano Zanuso. (2012) Validation of the Mywellness Key in Walking and Running Speeds. Journal of Sports Science and Medicine(11), 57 - 63.
This study was performed to assess the validity of the MyWellness Key (MWK) accelerometer during a treadmill-based protocol. The identification of different exercise intensities is imperative to objectively measure time spent at a specified exercise intensity. Thirty subjects, 15 men and 15 women (age = 24.5 ± 2.6 years; body mass index = 22.5 ± 2.5 kg·m-1), participated in a 4-phase treadmill protocol (5 minutes each one) using three different walking velocities (3, 4.5, and 6 km·h-1) and run (8 km·h-1) while outfitted with a MWK uniaxial accelerometer. Oxygen consumption was measured by indirect calorimetry (ICVO2). Results: The relationship between VO2 predicted from MWK (MWKVO2) and oxygen consumption (VO2 (ICVO2)), yielded a high and significant correlation (r = 0. 944; p < 0.001) with standard error of estimate (SEE) = 2.42 mL·kg-1·min-1. The average differences between the two methods (MWKVO2 - ICVO2) were -0.79 (-8. 8% at 3 km·h-1), -0.02 (-0.2% at 4.5 km·h-1), 0.51 (3.3% at 6 km·h-1) and -0.74 (-2.7% at 8 km·h-1) ml·kg-1·min-1. Only the 3 km·h-1 speed showed a difference when compared to the criterion measure (p < 0.001). Bland and Altman analysis revealed less than a 1 MET difference in the mean at each point estimate and relatively tight distribution with the standard errors, especially with the 2 moderate walking speeds. Conclusions: We found a high correlation between oxygen utilization and the MWK with low standard errors estimates. This indicates that this accelerometer can be used to identify exercise intensities that are related to walking and running.
First laboratory validation of a new uniaxial accelerometer, the MyWellness Key.
Results indicate a good exercise intensity prediction during walking at moderate to high speeds.
Comparing with other laboratory validations, MyWellness Key exercise intensity detection is aligned with other accelerometers.
MyWellness Key can be used to give valid measurements for a range of ambulatory activity in addition to the capabilities to give real-time feedback to the participant in health promotion studies.
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