Positive and Negative Work Efficiencies During Walking: A Comparison of Methods

Background: The metabolic cost of walking reflects the energy required to move the body over a given distance. Standard measurement methods require prolonged exertion from participants, which is not always feasible. Estimating instantaneous metabolic cost is valuable for real-time control of assistive devices such as exoskeletons or prostheses. This can be achieved by computing mechanical work and applying separate efficiencies to positive and negative work. Objective: This study aimed to compute and compare positive and negative work efficiencies using four different methods. A second objective was to evaluate how well metabolic cost, estimated from joint mechanical work weighted by these efficiencies, matched measured values. Method: Eleven participants walked on slopes of +/- 24%, +/- 12%, +/- 8% and level. The +/- 24% slopes were used to represent conditions of predominantly positive (ascent) and negative (descent) work. Mechanical work and efficiencies were calculated using four methods: potential energy (PE), combined limb (CLM), individual limb (ILM), and summed joint (& sum;joints). Metabolic costs estimated from summed joint work, adjusted by the efficiency pairs, were then compared to measured metabolic costs on intermediate slopes. Results: Results showed that efficiencies - particularly for negative work - depended on the mechanical work calculation method (negative efficiency range: -0.91 to -1.08). Despite this, all methods showed strong correlations with measured metabolic cost (r >= 0.97). Moreover, positive efficiency had a greater influence on the estimated metabolic cost than negative efficiency. Discussion: Efficiencies derived from the CLM, ILM, and & sum;joints methods more accurately captured changes between conditions than those obtained from the PE method, suggesting these methods are preferable. Future studies should assess their relevance in other contexts, such as load carriage or speed variations. (c) 2026 AGBM. Published by Elsevier Masson SAS. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).