Walking energy expenditure: A loaded approach to algorithm development

Abstract

Sensor-based predictions for walking energy expenditure require sufficiently versatile algorithms to generalize to a variety of conditions. Here we test whether our height-weight-speed (HWS) model validated across speed under level conditions is similarly accurate for loaded walking. We hypothesized that increases in walking energy expenditure would be proportional to added load when resting metabolism was subtracted from gross walking metabolism. After subtracting resting metabolic rate, walking energy expenditure was found to increase in direct proportion to load at walking speeds of 0.6, 1.0, and 1.4 m·s-1. With load carriage treated as body weight, the predictive algorithms derived using the HWS model were similar for loaded and unloaded conditions. Determination of the direct relationship between load and energy expenditure for level walking provides insight which may be used to refine algorithms, such as the HWS model, for use in body sensors to monitor physiological status in the field.