Evaluating dynamic similarity of fixed, self-selected and anatomically scaled speeds in non-linear analysis of gait during treadmill running

Objectives: The aim of this study is to evaluate how speed affects non-linear measures of variability. Fixed and self-selected speeds were compared to an anatomically scaled speed calculated based on leg length to evaluate which provided a more reproducible result between subjects. Methods: Sixteen subjects ran on a treadmill at a fixed, calculated and self-selected speed and at ±10% in each case. Kinematic data were collected for two minutes at 250Hz for each trial. Sample entropy (SaEn) and maximum Lyapunov exponents (LyE) were calculated from the sagittal knee and hip joint angles to evaluate rigidity of gait and local stability. These nonlinear measures were compared to evaluate the dynamic similarity of the movement in each case, and to evaluate speed as a confounding variable in non-linear analysis. Results: An anatomically scaled speed shows more dynamic similarity than a fixed or self-selected speed with the lowest observed coefficient of variation for each measure. This was found to be statistically significant for both nonlinear measures of the hip (SaEn p=0.038; LyE p=0.040). Speed was not found to be a confounding variable in non-linear analysis of running gait of a healthy population (2 < 0.05). Conclusions: Changes in speed by ±10% do not significantly affect stability and variability of gait for healthy participants, suggesting that they make adaptations to ensure optimal gait variability. Anatomically scaled speeds provide a more reliable methodology for both linear and non-linear analysis by providing a definitive protocol, suggesting it could replace self-selected or fixed speeds in future research.