Objectives: This investigation assessed the accuracy of error of the Pandolf load carriage energy expenditure equation when simulating contemporary military conditions (load distribution, external load and walking speed).
Design: Within-participant design.
Methods: Sixteen male participants completed 10 trials comprised of five walking speeds (2.5, 3.5, 4.5, 5.5 and 6.5km·h) and two external loads (22.7 and 38.4kg).
Results: The Pandolf equation demonstrated poor predictive precision, with a mean bias of 124.9W and -48.7 to 298.5W 95% limits of agreement. Furthermore, the Pandolf equation systematically under-predicted metabolic rate (p<0.05) across the 10 speed-load combinations. Predicted metabolic rate error ranged from 12-33% across all conditions with the 'moderate' walking speeds (i.e. 4.5-5.5km·h) yielding less prediction error (12-17%) when compared to the slower and faster walking speeds (21-33%).
Conclusions: Factors such as mechanical efficiency and load distribution contribute to the impaired predictive accuracy. The authors suggest the Pandolf equation should be applied to military load carriage with caution.
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http://dx.doi.org/10.1016/j.jsams.2017.08.009 | DOI Listing |
J Appl Physiol (1985)
October 2021
Biophysics and Biomodeling Division, United States Army Research Institute for Environmental Medicine, Natick, Massachusetts.
We addressed a practical question that remains largely unanswered after more than a century of active investigation: can equations developed in the laboratory accurately predict the energy expended under free-walking conditions in the field? Seven subjects walked a field course of 6,415 m that varied in gradient (-3.0 to +5.0%) and terrain (asphalt, grass) under unloaded (body weight only, ) and balanced, torso-loaded (1.
View Article and Find Full Text PDFBackground: The purpose of this study was to investigate the accuracy of the published prediction equations for determining level overground walking energy cost in young adults.
Methods: In total, 148 healthy young adults volunteered to participate in this study. Resting metabolic rate and energy expenditure variables at speeds of 4, 5, and 6 km/h were measured by indirect calorimetry, walking energy expenditure was estimated by 3 published equations.
Eur J Appl Physiol
September 2020
Department of Human Physiology, Gonzaga University, Spokane, USA.
Purpose: The purpose of this study was to develop and validate a data-supported prediction equation (Lankford equation) for walking metabolic cost ([Formula: see text]), and to compare this equation to the ACSM, Pandolf, Minetti, and LCDA equations. The current study also investigated how kinematics of incline walking relates to mechanical efficiency and metabolic cost.
Method: Subjects consisted of 145 recreationally fit individuals.
J Strength Cond Res
May 2022
Occupational Performance Research Group, Institute of Sport, University of Chichester, Chichester, United Kingdom.
Vine, CA, Coakley, SL, Blacker, SD, Doherty, J, Hale, B, Walker, EF, Rue, CA, Lee, BJ, Flood, TR, Knapik, JJ, Jackson, S, Greeves, JP, and Myers, SD. Accuracy of metabolic cost predictive equations during military load carriage. J Strength Cond Res 36(5): 1297-1303, 2022-To quantify the accuracy of 5 equations to predict the metabolic cost of load carriage under ecologically valid military speed and load combinations.
View Article and Find Full Text PDFAppl Ergon
January 2019
Oak Ridge Institute for Science and Education (ORISE), 1299 Bethel Valley Rd, Oak Ridge, TN, 37830, USA; Biophysics and Biomedical Modeling Division, United States Army Research Institute of Environmental Medicine, Natick, MA, 01760, USA.
Background: Predicting the energy costs of human travel over snow can be of significant value to the military and other agencies planning work efforts when snow is present. The ability to quantify, and predict, those costs can help planners determine if snow will be a factor in the execution of dismounted tasks and operations. To adjust predictive models for the effect of terrain, and more specifically for surface conditions, on energy costs, terrain coefficients (ƞ) have been developed.
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