Running spatio-temporal parameter variability - "Stride" package

R scripts (package "Stride") used to process data on spatio-temporal running parameters (step time TS, flight time TV, contact time TC, duty factor DF, cadence C and estimated vertical leg stiffness Kleg) obtained using an Optogait system (Optogait, Microgate, Bolzano, Italy). The scripts synthesise and clean the data and then calculate various variability indices as a function of the length of the time series. Linear (coefficient of variation, standard deviation) and non-linear (coefficient alpha 1 of detrend fluctuation analysis, Higuchi fractal index, box counting algorithm) cycle-by-cycle analyses are performed according to the calculation recommendations (Phinyomark et al. DOI :10.3389/fphys.2020.00333). The processing is done in several steps: first, the time series are extracted and outliers are managed, then analyses by time series and series size are performed , and finally the data are concatenated . An example of a dataset obtained using this procedure is attached (concatenated_files_12.xls). It contains a data set from 25 subjects who ran on a treadmill (Medical Treadmill, MONARK, Sverige) for 3 sessions of 6 minutes each, 24 hours apart. All subjects were trained to run on a treadmill. All participants ran more than twice a week for at least two years. Their age ranged between (20-36) years, body mass index (18.3-24.5) kg/m², running experience (3-15) years, kilometres run per year (1000-2500) km. This data set was collected as part of an ethics committee approved study (RCB number ID-RCB: 2019-A03012-55). Outlier detection was performed according to previously published values (García-Pinillos et al. DOI: 10.2478/hukin-2019-0098), obtained with the same instrument. Outlier management was performed using the imputeTS package, which has been validated for outlier management in biological time series. (http://cran.r-project.org/package=imputeTS ; http://cran.r-project.org/web/packages/imputeTS/imputeTS.pdf)