Abstract

Comparing clinical gait analysis (CGA) data between clinical centers is critical in the treatment and rehabilitation progress. However, CGA protocols and system configurations, as well as choice of marker sets and individual variability during marker attachment, may affect the comparability of data. The aim of this study was to evaluate reliability of CGA data collected between two gait analysis laboratories. Three healthy subjects underwent a standardized CGA protocol at two separate centers. Kinematic data were captured using the same motion capturing systems (two systems, same manufacturer, but different analysis software and camera configurations). The CGA data were analyzed by the same two observers for both centers. Interobserver reliability was calculated using single measure intraclass correlation coefficients (ICC). Intraobserver as well as between-laboratory intraobserver reliability were assessed using an average measure ICC. Interobserver reliability for all joints (ICCtotal = 0.79) was found to be significantly lower (p < 0.001) than intraobserver reliability (ICCtotal = 0.93), but significantly higher (p < 0.001) than between-laboratory intraobserver reliability (ICCtotal = 0.55). Data comparison between both centers revealed significant differences for 39% of investigated parameters. Different hardware and software configurations impact CGA data and influence between-laboratory comparisons. Furthermore, lower intra- and interobserver reliability were found for ankle kinematics in comparison to the hip and knee, particularly for interobserver reliability.

Highlights

  • Three-dimensional clinical gait analysis (CGA) is an important diagnostic tool within the field of movement disorders [1]

  • The results of this study showed higher intraobserver reliability than interobserver reliability for CGA data conducted in a single gait analysis laboratory

  • There was weaker intra- and interobserver reliability ankle kinematics when compared to the hip and knee

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Summary

Introduction

Three-dimensional clinical gait analysis (CGA) is an important diagnostic tool within the field of movement disorders [1]. Despite applied standardized protocols (e.g., marker-set, measurement pipeline), incompatibilities and discrepancies within CGA data of the same patient cohorts collected by different institutions are often observed, and have caused reservations concerning the applicability of CGA among multicenter studies [3,4,8]. Ferrari et al [4] compared the trunk, pelvis and lower limb kinematics of five separate measurement protocols (different marker sets), using a single data pool of subjects. These authors reported good correlations between kinematic variables in the sagittal plane (flexion/extension), but poorer correlations for out-of-sagittal-plane rotations, such as knee abduction/adduction. Model conventions and definitions are crucial for data comparison

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