Accuracy of the Energy Expenditure During Uphill Exercise Measured by the Waist-worn ActiGraph

Background/objective: The application of Micro-Electro-Mechanical Sensors (MEMS) as measurements of energy expenditure (EE) has certain disadvantages. For example, the inertial sensors cannot easily distinguish changes in ground slope during walking/running conditions, so the accuracy of EE calculation is biased. To resolve this issue, heart rate (HR) and heart rate reserve (HRR) were used as compensatory factors respectively to correct the classical empirical formula of the accelerometer analyzer for EE in this study.

Methods: To explore the improvement of the accuracy of EE during uphill exercise and compare the correction levels between HR and HRR, oxygen uptake was used as a criterion measure (CM). Thirty healthy adult males wore an ActiGraph GT3X with the Polar HR monitor and Vmax indirect calorimeter during twelve treadmill activities (3 gradients and 4 speeds).

Results: When the slopes were increased by 0%, 3%, and 6%, the measurement accuracy of the accelerometers, calculated by intraclass correlation coefficient (ICC), decreased by 0.877, 0.755, and 0.504, respectively (p < 0.05). The HR and HRR parameters of linear regression were used to correct the classical formula. The results showed that HR had higher coefficients of determination (R2) (0.801, 0.700, and 0.642 respectively) and ICCs (0.887, 0.825, and 0.785 respectively) than did the accelerometer outputs. HRR showed the highest coefficients of determination (R2) (0.821, 0.728, and 0.656 respectively) and ICCs (0.901, 0.844, and 0.795 respectively).

Conclusions: Through adding HRR parameters, the accuracy of the classical prediction formula EE was significantly improved during walking/running on sloping ground.