# The functional gait deviation index

## TL;DR

Researchers developed a new index to measure gait abnormalities by considering smoothness and joint interactions, which can be used to assess walking disorders more effectively.

## Contribution

The FGDI introduces a novel method that accounts for smoothness and co-variation in gait analysis.

## Key findings

- FGDI scales with overall gait function and provides a consistent measure of gait abnormality.
- FGDI is implemented as an interactive web app for easy use.
- FGDI improves upon existing benchmarks by incorporating joint/plane smoothness and co-variation.

## 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 component 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.