The Functional Gait Deviation Index

TL;DR

The paper introduces the functional gait deviation index (FGDI), a new measure for quantifying gait abnormality that accounts for movement smoothness and joint co-variation, improving gait analysis accuracy.

Contribution

It proposes the FGDI, a novel multivariate functional principal components analysis-based index that enhances gait abnormality measurement over existing benchmarks.

Findings

FGDI correlates with overall gait function

FGDI provides consistent gait abnormality measurement

FGDI is easily implemented via a web app

Abstract

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.