Elastic energy savings and active energy cost in a simple model of running

PLoS Comput Biol. 2021 Nov 23;17(11):e1009608. doi: 10.1371/journal.pcbi.1009608. eCollection 2021 Nov.

Abstract

The energetic economy of running benefits from tendon and other tissues that store and return elastic energy, thus saving muscles from costly mechanical work. The classic "Spring-mass" computational model successfully explains the forces, displacements and mechanical power of running, as the outcome of dynamical interactions between the body center of mass and a purely elastic spring for the leg. However, the Spring-mass model does not include active muscles and cannot explain the metabolic energy cost of running, whether on level ground or on a slope. Here we add explicit actuation and dissipation to the Spring-mass model, and show how they explain substantial active (and thus costly) work during human running, and much of the associated energetic cost. Dissipation is modeled as modest energy losses (5% of total mechanical energy for running at 3 m s-1) from hysteresis and foot-ground collisions, that must be restored by active work each step. Even with substantial elastic energy return (59% of positive work, comparable to empirical observations), the active work could account for most of the metabolic cost of human running (about 68%, assuming human-like muscle efficiency). We also introduce a previously unappreciated energetic cost for rapid production of force, that helps explain the relatively smooth ground reaction forces of running, and why muscles might also actively perform negative work. With both work and rapid force costs, the model reproduces the energetics of human running at a range of speeds on level ground and on slopes. Although elastic return is key to energy savings, there are still losses that require restorative muscle work, which can cost substantial energy during running.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Energy Metabolism
  • Humans
  • Models, Biological
  • Running*

Grants and funding

This work was funded by the Dr. Benno Nigg Research Chair (ADK) and the National Sciences and Engineering Research Council of Canada (https://www.nserc-crsng.gc.ca/; NSERC CRC, Tier 1 to ADK; NSERC Discovery to ADK). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.