Fractal analysis of muscle activity patterns during locomotion: pitfalls and how to avoid them

Despite the lack of consensus on how to perform fractal analysis of physiological time series, many studies rely on this technique. Here, we shed light on the potential pitfalls of using the Higuchi’s fractal dimension (HFD) and the Hurst exponent (H). We expose and suggest how to solve the drawbacks of such methods when applied to data from normal and perturbed locomotion by combining <em>in vivo</em> recordings and computational approaches. In this supplementary data set we made available: a) the metadata file “metadata.dat”; b) the baseline signals file “baseline_data.RData”; c) the R script “fractal_analysis.R” to calculate the H and HFD of the baseline data and produce the log-log plots. Explanatory comments are profusely present throughout the script and in the metadata file.