# Natural variability can increase human walking metabolic costs and its implications to simulation-based metabolic estimation

## TL;DR

This study shows that natural variability in human walking increases metabolic costs and that ignoring this variability in simulations leads to inaccurate metabolic cost estimates.

## Contribution

The paper demonstrates that stride-to-stride variability increases metabolic costs and that simulations using averaged strides underestimate these costs.

## Key findings

- Using an averaged stride underestimates metabolic cost by about 2.5%.
- Random stride selection can mis-estimate metabolic cost by up to 15%.
- Increased sensory or motor noise raises both metabolic cost and variability in a feedback-controlled model.

## Abstract

Human walking contains variability due to small intrinsic perturbations arising from sensory or motor noise, or to promote motor learning. We hypothesize that such stride-to-stride variability may increase the metabolic cost of walking over and above a perfectly periodic motion, and that neglecting such variability in simulations may mis-estimate the metabolic cost. Here, we quantify the metabolic estimation errors accrued by neglecting the stride-to-stride variability using human data and a musculoskeletal model by comparing the cost of multiple strides of walking and the cost of a perfectly periodic stride with averaged kinematics and kinetics. We find that using an averaged stride underestimates the cost by approximately 2.5%, whereas using a random stride may mis-estimate the cost positively or negatively by up to 15%, ignoring the contribution of measurement errors to the observed stride-to-stride variability. As a further illustration of the cost increase in a simpler dynamical context, we use a feedback-controlled inverted pendulum walking model to show that increasing the sensory or motor noise increases the overall metabolic cost, as well as the variability of stride-to-stride metabolic costs, as seen with the musculoskeletal simulations. Our work establishes the importance of accounting for stride-to-stride variability when estimating metabolic costs from motion.