Accuracy of predictive equations for metabolic cost of locomotion while carrying external load

Adam W Potter, David P Looney, Laurie A Blanchard, Alexander P Welles, William R Santee


Introduction: Energy cost estimation of dismounted military movements is of significant importance for a number of reasons, including optimal performance planning and to ensure individual safety.  Predicting energy costs during military road marches, i.e., locomotion, requires insights into key factors such as: body mass, clothing, any additional load carried, walking velocity, surface grade, and other terrain features (e.g., pavement, gravel, snow).  Methods: Physiological measures and measures of oxygen uptake (VO2) were collected from nine individual Soldiers (age, 22 ± 4 (SD) y; wt, 76.44 ± 10.67  kg; ht, 175.00 ± 10.14 cm; body fat, 23.4 ± 5.8%; VO2max, 49.22 ± 3.33 ml•kg-1•min-1), during treadmill exercise in an environmental chamber.  Volunteers walked at two different work intensities, approximately 350 and 540 W: under warm-humid (air temperature (Ta) 25°C, 50% relative humidity (RH)), hot-humid (35°C, 70% RH), and hot-dry (40°C, 20% RH) environmental conditions.  Observed VO2 values, in W, were compared to predicted total energy costs from four predictive equations using the root mean square error (RMSE), mean absolute error (MAE), and correlation coefficient (R2) values.  Results: Analyses showed predictions were in close agreement with measured values, with RMSE ranging from 19.56 to 38.16 W, MAE from 15.71 to 28.9 W, and R2 from 0.86 to 0.96.  Conclusion: The results indicate that for the specified test conditions, metabolic estimation equations can be used to accurately predict energy expenditure of walking locomotion.  These equations accurately predict energy costs when individual differences exist in external load, walking velocity, moderate differences in grade increased surface grade, and different levels of thermal stress.


energy expenditure, exercise, predictive equations, modeling, human locomotion

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