Fractal Analyses of Gait Variability During a Marathon

Abstract

Detrended fluctuation analysis (DFA) and Higuchi’s fractal dimension (HG) have previously been used to characterise motor control during gait. However, there is limited evidence of either being applied to running gait within a race environment. The aims were to: i) examine statistical persistence and fractal dimension of stride dynamics during a marathon, and ii) explore the relationship between DFA and HG for running gait. Therefore, DFA and HG were applied to stride interval series of each km of the 2018 TCS New York Marathon. Results showed consistent persistence, variability, and fractal dimension of stride interval series throughout the marathon with no significant differences observed between the beginning, middle, and end of the Marathon. Moreover, HG was shown to correlate strongly with DFA, which may be useful in monitoring motor control using fractal analyses in real time, by decreasing computation time and improving robustness to changing time series lengths.