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
Caroline Lisee, Tom Birchmeier, Arthur Yan, Brent Geers, Kaitlin O’Hagan, Callum Davis and Christopher Kuenze
the variables were not normally distributed (Table 1 ). Therefore, Spearman rank correlation coefficients were used to evaluate the relationship between the kinetic and audio waveform characteristics. Spearman rank correlation coefficients were interpreted as very weak ( ρ < .30), weak ( ρ = .30
Robert W. Cox, Rodrigo E. Martinez, Russell T. Baker and Lindsay Warren
repeated measures correlation study was designed to determine if the Clinometer Smartphone Application™ would produce equivalent measurements to the Baseline Evaluation Instruments™ 12-1000 plastic goniometer. The University of Idaho Institutional Review Board granted approval for the study. Written
Theresa L. Miyashita and Paul A. Ullucci
this study was to investigate the cumulative effect of subconcussive impacts on minimum perception time, static visual acuity, gaze stability (GST), and dynamic visual acuity (DVA) scores. The researchers hypothesized a positive correlation between subconcussive impacts and vestibulo-ocular system
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
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
Kenji Kanazawa, Yoshihiro Hagiwara, Takuya Sekiguchi, Ryo Fujita, Kazuaki Suzuki, Masashi Koide, Akira Ando and Yutaka Yabe
to investigate correlations between ROM and CHL elasticity, by using shear-wave elastography evaluation, in order to verify and expand upon data suggesting that CHL elasticity decreases with age and influences ROM restrictions. Materials and Methods Subjects A total of 84 volunteers (39 men and 45
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
Tricia J. Hubbard, John E. Kovaleski and Thomas W. Kaminski
Measurement reliability is critical when new sports-medicine devices or techniques are developed.
To determine the reliability of laxity measurements obtained from an instrumented ankle arthrometer.
Intratester reliability was examined using a test–retest design, and intertester reliability was assessed using the measurements recorded by 2 different examiners on a separate group of participants.
Sports-medicine research laboratory.
40 participants with no history of ankle injury, equally divided across the 2 studies.
Laxity measurements included anteroposterior (AP) displacement during loading to 125 N. Inversion–eversion (I–E) rotation was tested during loading to 4000 N-mm. The measures were analyzed using intraclass correlation coefficients (ICCs) and dependent t tests.
Good to excellent ICCs (.80–.99) for intratester and intertester reliability. A significant difference in measures was observed between testers for both AP displacement and I–E rotation.
Laxity measurements from an instrumented ankle arthrometer are reliable across test days and examiners
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.