  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.
