Data processing and statistics
REGRESSION
US data and ROM measurements of the dynamometer, as well as EMG data, were synchronized using a common digital interface (AcqKnowledge, Biopac Systems Inc., Goleta, CA, United States). Unwanted muscle activity was detected using the internal function of the used software package (AcqKnowledge, Biopac Systems Inc., Goleta, CA, United States). Specifically, under resting conditions, the mean and standard deviation of the EMG signal were determined over a 0.25 s period. Based on the algorithm of Hodges and BuiA paired t-test was performed in order to reveal systematic differences between the two testing conditions, thus evaluating the first hypothesis (higher fascial displacement in the condition with the knee extended). Effect sizes of significant differences were calculated and interpreted according to CohenFor the second hypothesis (possible relationship between ankle motion and displacement of dorsal thigh’s soft tissue), we used linear regression for parametric data and linear regression with bootstrapping for non-parametric data with BCa (Bias Corrected and accelerated) procedures. The dependent variable was displacement of the soft tissue of the SM and ankle ROM / GM aponeurosis displacement were selected as the predictors. Again, effect sizes were calculated according to Cohen