An important aspect of the study of multi-degree-of-freedom motor control is the analysis of high-dimensional variance data. Through the “uncontrolled manifold” (UCM) approach the structure in such data can be discovered and interpreted. The covariation by randomization (CR) approach provides nonlinear and potentially multi-dimensional measures of covariance. We critically examine these two approaches and compare them relative to the three fundamental issues of choice of variables, choice of model, and adoption of either a geometrical or a correlational view of variance. The UCM approach is a geometrical approach that seeks to discover the structure of variance in multi-degree-of-freedom task spaces in which all degrees of freedom have a common metric. The structure of variance in that space is interpreted in terms of its meaning for task variables. The CR approach seeks to uncover correlations between interpretable elemental variables. It requires a defined and common metric in the space of task variables, but not the elemental variables. Although the CR approach is better suited for systems with strong nonlinearities, variance structure that is not caused by correlation but by different amounts of variance in the different elemental variables is undetected by this approach.
Gregor Schöner and John P. Scholz
Katja Krustrup Pedersen, Esben Lykke Skovgaard, Ryan Larsen, Mikkel Stengaard, Søren Sørensen and Kristian Overgaard
, & Pfeiffer, 2016 ). However, it remains to be determined whether there is a correlation between accelerometer output and oxygen consumption (VO 2 , ml·min −1 ·kg −1 ) during high-speed running. It has been proposed that the plateau phenomenon is caused by the built-in filtering of the accelerometer signals
Francisco J. Vera-Garcia, Diego López-Plaza, Casto Juan-Recio and David Barbado
Stable and Unstable Sitting Test) and field settings (Biering-Sørensen Test, 3-Plane Core Strength Test, and Double-Leg Lowering Test). In addition, in order to avoid the potential bias caused by the low consistency of the variables on the correlational analysis, 25 , 26 the relative and absolute
Pedro Figueiredo, George P. Nassis and João Brito
and sample mean correlations. In repeated-measures studies, it is important to quantify within-subject correlations by modeling the longitudinal data set as a whole and by reducing the variation between subjects. 5 Therefore, the aim of this study was to quantify the correlation between the sIgA and
Charilaos Papadopoulos, J. Andrew Doyle and Brian D. LaBudde
The purpose of this study was to determine the relationship between various lactate-threshold (LT) definitions and the average running velocity during a 10-km and a 21.1-km time trial (TT).
Thirteen well-trained runners completed an incremental maximal exercise test, a 10-km TT, and a 21.1-km TT on a motorized treadmill. Blood samples were collected through a venous catheter placed in an antecubital vein. Pearson's correlation coefficients were used to determine the relationship between the running velocity at the different LT definitions and the average running velocity during each TT. A dependent t test was used to determine statistical differences for the mean lactate response between the 2 running distances.
The LTDmax, the point on the regression curve that yielded the maximal perpendicular distance to the straight line formed by the 2 endpoints, was the LT definition with the highest correlation for both 10-km (r = .844) and 21.1-km TTs (r = .783). The velocity at the LTDmax was not, however, the velocity closest to the performance velocity for either distance. The mean running velocity at each LT was significantly different and tended to overestimate the mean TT performance velocities. The mean lactate concentration during the 10-km TT (3.52 ± 1.58 mmol) was significantly higher than during the 21.1-km TT (1.86 ± 0.90 mmol).
These results indicate that a single LT point cannot be reliably associated with different running distances. Furthermore, these data suggest that a different methodology for estimating the LT that considers individual responses might be required for different running distances.
Durva Vahia, Adam Kelly, Harry Knapman and Craig A. Williams
effort. This method is easy to implement and provides a cost-effective and efficient alternative to HR measures ( 14 , 24 , 25 ). Many studies have investigated the use of sRPE scale as a measure of ITL in soccer ( 1 , 2 , 6 , 7 , 9 , 11 , 18 , 20 , 24 , 25 ). These studies measured the correlation
Mehmet Uygur, Goran Prebeg and Slobodan Jaric
We compared two standard methods routinely used to assess the grip force (GF; perpendicular force that hand exerts upon the hand-held object) in the studies of coordination of GF and load force (LF; tangential force) in manipulation tasks. A variety of static tasks were tested, and GF-LF coupling (i.e., the maximum cross-correlation between the forces) was assessed. GF was calculated either as the minimum value of the two opposing GF components acting upon the hand-held object (GFmin) or as their average value (GFavg). Although both methods revealed high GF-LF correlation coefficients, most of the data revealed the higher values for GFavg than for GFmin. Therefore, we conclude that the CNS is more likely to take into account GFavg than GFmin when controlling static manipulative actions as well as that GFavg should be the variable of choice in kinetic analyses of static manipulation tasks.
Erin Strutz, Raymond Browning, Stephanie Smith, Barbara Lohse and Leslie Cunningham-Sabo
in one group will precipitate PA changes in the other group. Thus, for such interventions to be successful, a significant positive correlation between parent and child PA must exist. Previous explorations that have examined the correlation between parent and child PA levels using direct observation
Kim Hébert-Losier, Kurt Jensen and Hans-Christer Holmberg
Jumping and hopping are used to measure lower-body muscle power, stiffness, and stretch-shortening-cycle utilization in sports, with several studies reporting correlations between such measures and sprinting and/or running abilities in athletes. Neither jumping and hopping nor correlations with sprinting and/or running have been examined in orienteering athletes.
The authors investigated squat jump (SJ), countermovement jump (CMJ), standing long jump (SLJ), and hopping performed by 8 elite and 8 amateur male foot-orienteering athletes (29 ± 7 y, 183 ± 5 cm, 73 ± 7 kg) and possible correlations to road, path, and forest running and sprinting performance, as well as running economy, velocity at anaerobic threshold, and peak oxygen uptake (VO2peak) from treadmill assessments.
During SJs and CMJs, elites demonstrated superior relative peak forces, times to peak force, and prestretch augmentation, albeit lower SJ heights and peak powers. Between-groups differences were unclear for CMJ heights, hopping stiffness, and most SLJ parameters. Large pairwise correlations were observed between relative peak and time to peak forces and sprinting velocities; time to peak forces and running velocities; and prestretch augmentation and forest-running velocities. Prestretch augmentation and time to peak forces were moderately correlated to VO2peak. Correlations between running economy and jumping or hopping were small or trivial.
Overall, the elites exhibited superior stretch-shortening-cycle utilization and rapid generation of high relative maximal forces, especially vertically. These functional measures were more closely related to sprinting and/or running abilities, indicating benefits of lower-body training in orienteering.
Niell G. Elvin, Alex A. Elvin, Steven P. Arnoczky and Michael R. Torry
Impact forces and shock deceleration during jumping and running have been associated with various knee injury etiologies. This study investigates the influence of jump height and knee contact angle on peak ground reaction force and segment axial accelerations. Ground reaction force, segment axial acceleration, and knee angles were measured for 6 male subjects during vertical jumping. A simple spring-mass model is used to predict the landing stiffness at impact as a function of (1) jump height, (2) peak impact force, (3) peak tibial axial acceleration, (4) peak thigh axial acceleration, and (5) peak trunk axial acceleration. Using a nonlinear least square fit, a strong (r = 0.86) and significant (p ≤ 0.05) correlation was found between knee contact angle and stiffness calculated using the peak impact force and jump height. The same model also showed that the correlation was strong (r = 0.81) and significant (p ≤ 0.05) between knee contact angle and stiffness calculated from the peak trunk axial accelerations. The correlation was weaker for the peak thigh (r = 0.71) and tibial (r = 0.45) axial accelerations. Using the peak force but neglecting jump height in the model, produces significantly worse correlation (r = 0.58). It was concluded that knee contact angle significantly influences both peak ground reaction forces and segment accelerations. However, owing to the nonlinear relationship, peak forces and segment accelerations change more rapidly at smaller knee flexion angles (i.e., close to full extension) than at greater knee flexion angles.