Abstract
BACKGROUND: Physical inactivity remains the largest risk factor for the development of cardiovascular disease worldwide. Wearable devices have become a popular method of measuring activity-based outcomes and facilitating behavior change to increase cardiorespiratory fitness (CRF) or maximal oxygen consumption (VO(2max)) and reduce weight. However, it is critical to determine their accuracy in measuring these variables. OBJECTIVE: This study aimed to determine the accuracy of using a smartphone and the application Myworkout GO for submaximal prediction of VO(2max). METHODS: Participants included 162 healthy volunteers: 58 women and 104 men (17-73 years old). The study consisted of 3 experimental tests randomized to 3 separate days. One-day VO(2max) was assessed with Metamax II, with the participant walking or running on the treadmill. On the 2 other days, the application Myworkout GO used standardized high aerobic intensity interval training (HIIT) on the treadmill to predict VO(2max). RESULTS: There were no significant differences between directly measured VO(2max) (mean 49, SD 14 mL/kg/min) compared with the VO(2max) predicted by Myworkout GO (mean 50, SD 14 mL/kg/min). The direct and predicted VO(2max) values were highly correlated, with an R(2) of 0.97 (P<.001) and standard error of the estimate (SEE) of 2.2 mL/kg/min, with no sex differences. CONCLUSIONS: Myworkout GO accurately calculated VO(2max), with an SEE of 4.5% in the total group. The submaximal HIIT session (4 x 4 minutes) incorporated in the application was tolerated well by the participants. We present health care providers and their patients with a more accurate and practical version of health risk estimation. This might increase physical activity and improve exercise habits in the general population.