approximately 10% during front crawl swimming. Thus, practical CoM velocity estimation methods, using a minimal effort, are needed for the analysis of front crawl swimming. During the front crawl, swimmers move their right and left arms alternately, and the velocity of the arm movement in swimming direction is
Yuji Matsuda, Yoshihisa Sakurai, Keita Akashi and Yasuyuki Kubo
LeRoy W. Alaways, Sean P. Mish and Mont Hubbard
Pitched-baseball trajectories were measured in three dimensions during competitions at the 1996 Summer Olympic games using two high-speed video cameras and standard DLT techniques. A dynamic model of baseball flight including aerodynamic drag and Magnus lift forces was used to simulate trajectories. This simulation together with the measured trajectory position data constituted the components of an estimation scheme to determine 8 of the 9 release conditions (3 components each of velocity, position, and angular velocity) as well as the mean drag coefficient CD and terminal conditions at home plate. The average pitch loses 5% of its initial velocity during flight. The dependence of estimated drag coefficient on Reynolds number hints at the possibility of the drag crisis occurring in pitched baseballs. Such data may be used to quantify a pitcher’s performance (including fastball speed and amount of curve-ball break) and its improvement or degradation over time. It may also be used to understand the effects of release parameters on baseball trajectories.
Kayla J. Nuss, Joseph L. Sanford, Lucas J. Archambault, Ethan J. Schlemer, Sophie Blake, Jimikaye Beck Courtney, Nicholas A. Hulett and Kaigang Li
to an inaccurate HR reading, these consumers may be at risk for cardiac complications ( Karvonen & Vuorimaa, 1988 ; Thompson, Arena, Riebe, & Pescatello, 2013 ). Other groups also benefit from accuracy in HR estimation. In both elite athletes and recreational exercisers, HR monitors have been
Yoshifumi Kijima, Ryoji Kiyama, Masaki Sekine, Toshiyo Tamura, Toshiro Fujimoto, Tetsuo Maeda and Tadasu Ohshige
-axial accelerometer . Gait & Posture, 30 ( 1 ), 60 – 64 . PubMed doi:10.1016/j.gaitpost.2009.02.017 10.1016/j.gaitpost.2009.02.017 Moe-Nilssen , R. , & Helbostad , J.L. ( 2004 ). Estimation of gait cycle characteristics by trunk accelerometry . Journal of Biomechanics, 37 ( 1 ), 121 – 126 . PubMed doi:10
Kenneth R. Fox, Charles B. Corbin and William H. Couldry
The Psychological Model for Physical Activity Participation and the Physical Estimation and Attraction Scales (PEAS) were developed by Sonstroem using adolescent male subjects. This study investigated the adequacy of the model and instrument for explaining the involvement of college-age females in physical activity. Results indicated that although the model worked similarly for both sexes, there were important differences. Attraction to physical activity, as measured by the Attraction scale, does not contribute to the model for the females in this study, but it does for males. Physical estimation emerged as a key factor, particularly for females, in its relationship with self-esteem, fitness, and physical activity levels. The Estimation Scale appears to be a reliable and powerful instrument for assessing this construct. Future application and development of the model and scales is discussed.
Daniel Cury Ribeiro, Joelly Mahnic de Toledo, Roberto Costa Krug and Jefferson Fagundes Loss
Shoulder injuries are often related to rotator cuff muscles. Although there are various models for muscle force estimation, it is difficult to ensure that the results obtained with such models are reliable. The aim of the current study was to compare two models of muscle force estimation. Eight subjects, seven male and one female (mean age of 24 yr; mean height of 1.83 m), performed five isokinetic maximum concentric contractions of internal and external shoulder rotation. Two models with different algorithms were used. In both, the input data consisted of the measured internal rotation moment. Comparisons were made between the difference and the average results obtained with each model of muscle force estimation. There was reasonable agreement among the results for force between the two models for subscapularis, pectoralis major, and anterior deltoideus muscles results. Conversely, poor correlation was found for the latissimus dorsi, teres major, and middle deltoid. These results suggest that the algorithm structure might have a strong effect on muscle force estimation results.
William G. Thorland, Glen O. Johnson and Terry J. Housh
Twenty national class, junior level, track and field competitors were measured for body density (BD) via underwater weighing corrected for residual lung volume, and for skinfold (SF) thicknesses, to determine the accuracy of anthropometric estimations of body composition in athletic adolescent black males. BD was transformed to fat-free body (FFB) weight values using the formulas of Brozek, Lohman (age-adjusted), and Schutte (young black men), respectively. For each SF equation, total error (TE) was highest with the formula of Lohman (2.31–4.14 kg) and lowest with the formula of Schutte (2.02–3.62 kg). TE was further reduced when SF estimates of BD were transformed to FFB via the formula of Brozek and were compared to criterion values of FFB based on the formula of Schutte (2.05–3.10 kg). Therefore, racial influences affecting hydrostatically determined FFB differed from those affecting anthropometric estimations.
Benjamin W. Infantolino, Daniel J. Gales, Samantha L. Winter and John H. Challis
The purpose of this study was to validate ultrasound muscle volume estimation in vivo. To examine validity, vastus lateralis ultrasound images were collected from cadavers before muscle dissection; after dissection, the volumes were determined by hydrostatic weighing. Seven thighs from cadaver specimens were scanned using a 7.5-MHz ultrasound probe (SSD-1000, Aloka, Japan). The perimeter of the vastus lateralis was identified in the ultrasound images and manually digitized. Volumes were then estimated using the Cavalieri principle, by measuring the image areas of sets of parallel two-dimensional slices through the muscles. The muscles were then dissected from the cadavers, and muscle volume was determined via hydrostatic weighing. There was no statistically significant difference between the ultrasound estimation of muscle volume and that estimated using hydrostatic weighing (p > 0.05). The mean percentage error between the two volume estimates was 0.4% ± 6.9. Three operators all performed four digitizations of all images from one randomly selected muscle; there was no statistical difference between operators or trials and the intraclass correlation was high (>0.8). The results of this study indicate that ultrasound is an accurate method for estimating muscle volumes in vivo.
Erich J. Petushek, Edward T. Cokely, Paul Ward and Gregory D. Myer
Instrument-based biomechanical movement analysis is an effective injury screening method but relies on expensive equipment and time-consuming analysis. Screening methods that rely on visual inspection and perceptual skill for prognosticating injury risk provide an alternative approach that can significantly reduce cost and time. However, substantial individual differences exist in skill when estimating injury risk performance via observation. The underlying perceptual-cognitive mechanisms of injury risk identification were explored to better understand the nature of this skill and provide a foundation for improving performance. Quantitative structural and process modeling of risk estimation indicated that superior performance was largely mediated by specific strategies and skills (e.g., irrelevant information reduction), and independent of domain-general cognitive abilities (e.g., mental rotation, general decision skill). These cognitive models suggest that injury prediction expertise (i.e., ACL-IQ) is a trainable skill, and provide a foundation for future research and applications in training, decision support, and ultimately clinical screening investigations.
Durva Vahia, Adam Kelly, Harry Knapman and Craig A. Williams
are heart rate (HR)-based estimations and perception of effort-based estimations ( 24 ). HR is a nonintrusive measure of physiological response and is monitored using HR transmitter belts worn by the players ( 26 ). HR demonstrates a nearly linear relationship with VO 2 over a wide range of steady