, Taiwan, China) 12 bit analogue-to-digital converter. Custom designed software was used Selleckchem BMS 907351 to extract the biomechanical parameters that define SQJ performance (achieved jump height, hjump) from the recorded vGRF-time curve. hjump was extracted using the body center of mass (BCM) vertical take-off velocity which was derived through the integration of the net vGRF. The analysis included only the best attempt, as indicated

with the adoption of the criterion described above. According to relative studies,22, 23, 24, 26 and 30 selected force and spatio-temporal parameters are included in PCA based on the fact that these parameters were found to represent the tendency of force- or time-dependency of SQJ performance. PCA is a mathematical procedure that investigates the variances of a set of variables

and it is used as a descriptive tool.34 PCA converts a large number of highly intercorrelated variables into a smaller number GW3965 research buy of linearly combined uncorrelated (i.e., “orthogonal”) computed factors named principal components. If a substantial correlation exists among the initial variables, the first principal components will account for most (approximately 70%–90%) of the variation of the original variables.34 Thus, the derived principal components preserve most of the information given by the initial variables. This procedure extracts a factor pattern matrix, in which the number of principal components is CYTH4 defined by the number of eigenvalues larger than 1. This is adopted because a principal component with a variance less than the above mentioned value contains less information than of the original variance (Kaiser’s rule).34 In order to rationalize the identification of the extracted factors, the factor pattern matrix is rotated using specific criterions (i.e., the loadings of the variables on the extracted factor) and a number of iterations of the procedure in a way that the original variables are eventually strongly related to one of the extracted principal

components. The use of PCA assists the acquisition of information about the force- or time-dependency of an individual’s jumping profile by reducing the large number of biomechanical parameters needed to express vertical jumping performance into the coordinates of the factor scores (the plot of the individual scores on the rotated principal components).22 Under this perspective, the following force and spatio-temporal parameters were calculated (Fig. 1): peak vGRF relative to body mass (FΖbm), peak power relative to body mass (Pbm), maximum rate of force development (RFDmax), impulse time (tC), time to achieve peak force (tFΖmax), and vertical BCM trajectory during the propulsion phase (SBCM). RFDmax was directly extracted as the first time derivative of the recorded vGRF.