example, cheerleading, swimming, or synchronized skating ( Reel & Gill, 1996 ). The attempt to standardize a weight pressures measure across sports originated with the validation of the English-language version of the weight pressures in sport for female athletes (WPS-F; Reel, Petrie, SooHoo, & Anderson
Clara Teixidor-Batlle, Carles Ventura Vall-llovera, Justine J. Reel and Ana Andrés
Samantha L. Winter, Sarah M. Forrest, Joanne Wallace and John H. Challis
-specific BSIPs, however, a key problem is that no female-specific geometric models for estimating BSIPs have been validated, despite significant differences in the shapes of segments between males and females. 3 There are several methods of estimating BSIPs. Scanning techniques such as dual x-ray absorptiometry
Ashley A. Hansen, Joanne E. Perry, John W. Lace, Zachary C. Merz, Taylor L. Montgomery and Michael J. Ross
treatment monitoring in sport psychological practice; therefore, the current study sought to create an instrument addressing this need. This research endeavor resulted in the development and initial psychometric validation of a 17-item self-report instrument that measures four dimensions of progress
James C. Martin, Douglas L. Milliken, John E. Cobb, Kevin L. McFadden and Andrew R. Coggan
This investigation sought to determine if cycling power could be accurately modeled. A mathematical model of cycling power was derived, and values for each model parameter were determined. A bicycle-mounted power measurement system was validated by comparison with a laboratory ergometer. Power was measured during road cycling, and the measured values were compared with the values predicted by the model. The measured values for power were highly correlated (R 2 = .97) with, and were not different than, the modeled values. The standard error between the modeled and measured power (2.7 W) was very small. The model was also used to estimate the effects of changes in several model parameters on cycling velocity. Over the range of parameter values evaluated, velocity varied linearly (R 2 > .99). The results demonstrated that cycling power can be accurately predicted by a mathematical model.
Fabio Bertapelli, Stamatis Agiovlasitis, Robert W. Motl, Roberto A. Soares, Marcos M. de Barros-Filho, Wilson D. do Amaral-Junior and Gil Guerra-Junior
al., 1996 ). Previous research has developed and cross-validated equations from BMI and simple demographic variables such as sex and age for predicting %BF in individuals without ID ( Deurenberg, Weststrate, & Seidell, 1991 ; Gallagher et al., 2000 ; Jackson et al., 2002 ). These equations, however, may
Paul M. Vanderburgh and Ronald E. DeMeersman
The 12-Minute Stationary Cycle Ergometer Test (12MCET) has been developed and validated as an accurate VO2peak prediction test particularly for the injured (7). Prediction is based on body weight and total work done in 12 min at a resistance setting of 2.5 kp (men) and 2.0 kp (women) on the Monark cycle ergometer. In the development of the 12MCET a small number of subjects stated a preference for a higher resistance setting than 2.5 kp. The purpose of this study was to validate the use of the 12MCET with a resistance setting of 3.0 kp for a sample of 30 college-age men. When applied to the 12MCET, use of the 3.0 kp resistance setting overpredicted actual VO2peak by a mean of 175 ml • min−1 (p = .02). We concluded that the use of a 3.0 kp resistance setting for the 12MCET is inappropriate and that any resistance setting other than that prescribed should not be used without proper validation.
Jonathan R. Kusins, Ryan Willing, Graham J.W. King and Louis M. Ferreira
A computational elbow joint model was developed with a main goal of providing complimentary data to experimental results. The computational model was developed and validated using an experimental elbow joint phantom consisting of a linked total joint replacement. An established in-vitro motion simulator was used to actively flex/extend the experimental elbow in multiple orientations. Muscle forces predicted by the computational model were similar to the experimental model in 4 out of the 5 orientations with errors less than 7.5 N. Valgus angle kinematics were in agreement with differences less than 2.3°. In addition, changes in radial head length, a clinically relevant condition following elbow reconstruction, were simulated in both models and compared. Both lengthening and shortening of the radial head prosthesis altered muscle forces by less than 3.5 N in both models, and valgus angles agreed within 1°. The computational model proved valuable in cross validation with the experimental model, elucidating important limitations in the in-vitro motion simulator’s controller. With continued development, the computational model can be a complimentary tool to experimental studies by providing additional noninvasive outcome measurements.
Jason S. Scibek and Christopher R. Carcia
The purpose of our study was to establish criterion-related validity and repeatability of a shoulder biomechanics testing protocol involving an electromagnetic tracking system (Flock of Birds [FoB]). Eleven subjects completed humeral elevation tasks in the sagittal, scapular, and frontal planes on two occasions. Shoulder kinematics were assessed with a digital inclinometer and the FoB. Intrasession and intersession repeatability for orthopedic angles, and humeral and scapular kinematics ranged from moderate to excellent. Correlation analyses revealed strong relationships between inclinometer and FoB measures of humeral motion, yet considerable mean differences were noted between the measurement devices. Our results validate use of the FoB for measuring humeral kinematics and establish our testing protocol as reliable. We must continue to consider factors that can impact system accuracy and the effects they may have on kinematic descriptions and how data are reported.
Jonathan G. Beckwith, Jeffrey J. Chu and Richard M. Greenwald
Although the epidemiology and mechanics of concussion in sports have been investigated for many years, the biomechanical factors that contribute to mild traumatic brain injury remain unclear because of the difficulties in measuring impact events in the field. The purpose of this study was to validate an instrumented boxing headgear (IBH) that can be used to measure impact severity and location during play. The instrumented boxing headgear data were processed to determine linear and rotational acceleration at the head center of gravity, impact location, and impact severity metrics, such as the Head Injury Criterion (HIC) and Gadd Severity Index (GSI). The instrumented boxing headgear was fitted to a Hybrid III (HIII) head form and impacted with a weighted pendulum to characterize accuracy and repeatability. Fifty-six impacts over 3 speeds and 5 locations were used to simulate blows most commonly observed in boxing. A high correlation between the HIII and instrumented boxing headgear was established for peak linear and rotational acceleration (r 2 = 0.91), HIC (r 2 = 0.88), and GSI (r 2 = 0.89). Mean location error was 9.7 ± 5.2°. Based on this study, the IBH is a valid system for measuring head acceleration and impact location that can be integrated into training and competition.
Erin Hanlon and Cynthia Bir
Soccer heading has been studied previously with conflicting results. One major issue is the lack of knowledge regarding what actually occurs biomechanically during soccer heading impacts. The purpose of the current study is to validate a wireless head acceleration measurement system, head impact telemetry system (HITS) that can be used to collect head accelerations during soccer play. The HIT system was fitted to a Hybrid III (HIII) head form that was instrumented with a 3-2-2-2 accelerometer setup. Fifteen impact conditions were tested to simulate impacts commonly experienced during soccer play. Linear and angular acceleration were calculated for both systems and compared. Root mean square (RMS) error and cross correlations were also calculated and compared for both systems. Cross correlation values were very strong with r = .95 ± 0.02 for ball to head forehead impacts and r = .96 ± 0.02 for head to head forehead impacts. The systems showed a strong relationship when comparing RMS error, linear head acceleration, angular head acceleration, and the cross correlation values.