Pribyslavska Veronika, Caputo Jennifer L, Coons John M, Barry Vaughn W
a Department of Health, Physical Education, and Sport Sciences , Arkansas State University , Jonesboro , AR , USA.
b Department of Health and Human Performance , Middle Tennessee State University , Murfreesboro , TN , USA.
J Med Eng Technol. 2018 May;42(4):265-273. doi: 10.1080/03091902.2018.1472823. Epub 2018 Jun 18.
To examine the accuracy of activity monitors in estimating energy expenditure (EE) during activities of varying mode and intensity and to evaluate the impact of including energy expended during recovery from activity (EPOC) on the EE estimate. EE estimates obtained from the Fitbit Surge (FBS), Garmin Vívofit (GV) and SenseWear Armband Mini (SWA) were compared to criterion EE with and without EPOC adjustments during moderate- and vigorous-intensity treadmill and cycling activities.
Participants (N = 34; 23 males) completed counterbalanced treadmill or cycling conditions, comprised of a resting metabolic rate measurement, 10-min bouts of moderate- and vigorous-intensity activity and an EPOC measurement. Participants simultaneously wore the three activity monitors and a portable metabolic analyser.
The FBS provided lowest percent error (PE) during treadmill walking (4.4%) and the GV during moderate (6.4%) and vigorous (-0.1%) cycling bouts. EPOC-adjusted PE was higher than non-EPOC PE across all monitors and activities. Mean absolute error rate (MAPE), indicating overall measurement error, was the smallest for the FBS (14.1%) during moderate treadmill walking and the largest for the SWA (53.5%) for vigorous intensity cycling. Only the FBS had comparable non-EPOC (14.6%) and EPOC-adjusted (17.6%) MAPE during treadmill walking.
The activity monitors tended to underestimate EE during moderate and vigorous treadmill and cycling activities. The EE estimates from the activity monitors did not account for the energy cost met by anaerobic means during activity, as suggested by the higher EPOC-adjusted EE error rates.
研究活动监测器在估计不同模式和强度活动期间能量消耗（EE）方面的准确性，并评估将活动恢复期间消耗的能量（EPOC）纳入EE估计的影响。将在中等强度和剧烈强度跑步机及骑行活动期间，通过Fitbit Surge（FBS）、佳明Vívofit（GV）和SenseWear Armband Mini（SWA）获得的EE估计值与有无EPOC调整的标准EE进行比较。
参与者（N = 34；23名男性）完成了平衡的跑步机或骑行测试，包括静息代谢率测量、10分钟的中等强度和剧烈强度活动以及一次EPOC测量。参与者同时佩戴这三种活动监测器和一台便携式代谢分析仪。
在跑步机行走期间，FBS的误差百分比（PE）最低（4.4%）；在中等强度（6.4%）和剧烈强度（-0.1%）骑行测试中，GV的PE最低。在所有监测器和活动中，经EPOC调整后的PE均高于未经EPOC调整的PE。表示总体测量误差的平均绝对误差率（MAPE），在中等强度跑步机行走期间，FBS最小（14.1%）；在剧烈强度骑行时，SWA最大（53.5%）。只有在跑步机行走期间，FBS的未经EPOC调整的MAPE（14.6%）和经EPOC调整的MAPE（17.6%）具有可比性。
在中等强度和剧烈强度的跑步机及骑行活动期间，活动监测器往往会低估EE。如经EPOC调整后的EE误差率较高所示，活动监测器的EE估计未考虑活动期间通过无氧方式消耗的能量成本。
