  A typical gait analysis requires the examination of the motion of nine joint
angles on the left-hand side and six joint angles on the right-hand side across
multiple subjects. Due to the quantity and complexity of the data, it is useful
to calculate the amount by which a subject's gait deviates from an average
normal profile and to represent this deviation as a single number. Such a
measure can quantify the overall severity of a condition affecting walking,
monitor progress, or evaluate the outcome of an intervention prescribed to
improve the gait pattern. The gait deviation index, gait profile score, and the
overall abnormality measure are standard benchmarks for quantifying gait
abnormality. However, these indices do not account for the intrinsic smoothness
of the gait movement at each joint/plane and the potential co-variation between
the joints/planes. Utilizing a multivariate functional principal components
analysis we propose the functional gait deviation index (FGDI). FGDI accounts
for the intrinsic smoothness of the gait movement at each joint/plane and the
potential co-variation between the joints. We show that FGDI scales with
overall gait function, provides a consistent measure of gait abnormality, and
is implemented easily using an interactive web app.
