Test-retest reliability of three dimensional gait analysis: Including a novel approach to visualising agreement of gait cycle waveforms with Bland and Altman plots

- Bland and Altman plots of gait waveforms are useful to visualise measurement error.
- Intra-rater reliability of kinetic and kinematic parameters is variable across planes.
- Temporal-spatial parameters of gait are highly reproducible.

Background/AimEstimating the measurement error (reliability) of three dimensional gait analysis (3DGA) is crucial to interpretation of gait data. The purpose of this study was to investigate the intra-rater reliability of 3DGA and apply a novel method of visualising reliability of gait cycle waveforms.MethodsA test re-test design was employed. A convenience sample of 30 healthy adults (18F; 12M: mean age 30 ± 6.8 years) participated. Subjects walked along a 10 m walkway at their preferred gait speed and 3DGA data were collected using a VICON® 3DGA system. Testing was performed by the same investigator on two separate days within two weeks. Data from 10 trials were averaged and analysed.AnalysisThe intraclass correlation coefficient (ICC), the standard error of measurement (SEM), minimal detectable change (MDC) and limits of agreement were calculated for kinetic and kinematic data. Bland and Altman plots were applied to gait cycle waveforms.ResultsSpatio-temporal parameters such as cadence, step length, velocity, step time and step width were highly repeatable generating ICC's of 0.90 and above and low SEM/MDC. Range of joint movement across the gait cycle was generally more reliable than either minimum or maximum values and higher ICCs were obtained for movement in the sagittal plane. For kinematic data the standard error of measurement was low (≤5̊) for the majority of parameters. Transverse plane measurements showed poor reliablility with lowest ICC's. ICCs for kinetic data ranged from 0.51 to 0.81.ConclusionsReliability of 3DGA has been estimated for our gait laboratory. Bland and Altman plots of gait cycle waveforms provide a useful addition to reliability analysis.