Walking dynamics are symmetric (enough)

TL;DR

This study investigates the symmetry assumption in human walking dynamics, finding significant asymmetries but demonstrating that models ignoring these asymmetries can be more consistent and predictive.

Contribution

The paper challenges the common assumption of symmetry in walking models by statistically testing for asymmetries and showing that ignoring them can improve model performance.

Findings

Significant asymmetries exist in human walking dynamics.

Ignoring asymmetries can lead to more consistent models.

Symmetry assumptions may not always enhance model accuracy.

Abstract

Many biological phenomena such as locomotion, circadian cycles, and breathing are rhythmic in nature and can be modeled as rhythmic dynamical systems. Dynamical systems modeling often involves neglecting certain characteristics of a physical system as a modeling convenience. For example, human locomotion is frequently treated as symmetric about the sagittal plane. In this work, we test this assumption by examining human walking dynamics around the steady-state (limit-cycle). Here we adapt statistical cross validation in order to examine whether there are statistically significant asymmetries, and even if so, test the consequences of assuming bilateral symmetry anyway. Indeed, we identify significant asymmetries in the dynamics of human walking, but nevertheless show that ignoring these asymmetries results in a more consistent and predictive model. In general, neglecting evident characteristics of a system can be more than a modeling convenience---it can produce a better model.