Quantifying gait parameters : number of strides needed to obtain reliable data in two-dimensional treadmill running gait analysis

Abstract

Gait quantification has been a subject of growing interest in the recent years and researchers are looking into the reliability of two-dimensional (2D) video-based gait analysis as a cheaper alternative. Despite the attempts to develop a standardised protocol for running gait analysis, there is a lack of consistency in data reporting and the absence of clear guidelines remains. This study aims to identify the minimum number of steps required to achieve steady state values that are representative of an individual’s gait pattern. It also aims to investigate the effects of an increasing number of steps on data reliability. It is hypothesised that reliability increases with the number of steps until data stabilisation has been achieved. Digital videos were taken from a sample of 14 recreational runners who participated in a single session of treadmill running. 30 strides per runner were recorded to extract data for 11 clinically relevant kinematic variables. These datasets were then further assessed using the sequential estimation technique (SET) and intraclass correlation coefficient (ICC) to determine the optimal number of steps and calculate reliability respectively. SET proposed that a minimum of 21 strides is needed to capture stable data across all parameters, while ICC revealed that reliability is not affected by the number of steps performed. Future researchers who wish to accurately quantify gait behaviour are recommended to consider the kinematic variables used in this study and include at least 21 strides in their experimental protocol.