Work

The functional gait deviation index

Year: 2025

Type: article

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.

Source: Journal of Applied Statistics

DOI: 10.1080/02664763.2025.2514150

Authors: Sajal Kaur Minhas, Morgan Sangeux, Julia Polak, Michelle Carey

Institutions: University College Dublin, University Children’s Hospital Basel, The University of Melbourne

Language: English

Topic: Advanced Statistical Methods and Models

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: hybrid

Funder: Science Foundation Ireland