Validity of sports watches when estimating energy expenditure during running

Abstract

Abstract Background The aim of this study was to assess the accuracy of three different sport watches in estimating energy expenditure during aerobic and anaerobic running. Methods Twenty trained subjects ran at different intensities while wearing three commercial sport watches (Suunto Ambit2, Garmin Forerunner920XT, and Polar V800). Indirect calorimetry was used as the criterion measure for assessing energy expenditure. Different formulas were applied to compute energy expenditure from the gas exchange values for aerobic and anaerobic running. Results The accuracy of the energy expenditure estimations was intensity-dependent for all tested watches. During aerobic running (4–11 km/h), mean absolute percentage error values of −25.16% to +38.09% were observed, with the Polar V800 performing most accurately (stage 1: −12.20%, stage 2: −3.61%, and stage 3: −4.29%). The Garmin Forerunner920XT significantly underestimated energy expenditure during the slowest stage (stage 1: −25.16%), whereas, the Suunto Ambit2 significantly overestimated energy expenditure during the two slowest stages (stage 1: 38.09%, stage 2: 36.29%). During anaerobic running (14–17 km/h), all three watches significantly underestimated energy expenditure by −21.62% to −49.30%. Therefore, the error in estimating energy expenditure systematically increased as the anaerobic running speed increased. Conclusions To estimate energy expenditure during aerobic running, the Polar V800 is recommended. By contrast, the other two watches either significantly overestimated or underestimated energy expenditure during most running intensities. The energy expenditure estimations generated during anaerobic exercises revealed large measurement errors in all tested sport watches. Therefore, the algorithms for estimating energy expenditure during intense activities must be improved before they can be used to monitor energy expenditure during high-intensity physical activities.

Keywords

• Wearables
• High-intensity
• Maximal accumulated oxygen deficit
• Validation
• Monitoring training