JAVELIN TRAJECTORY SIMULATION AND ITS USE IN COACHING

Scientific analysis and assessment of athletic performance are, in the general case, notoriously difficult. In track and field events there are at least clearly defined measures of performance (time expired, height jumped, distances thrown, etc.) . The coaches' job then becomes one of assisting the athlete to improve his or her technique in order to achieve the optimal performance possible within the constraints imposed by the physical limitations of the athlete. In addition, the coach can suggest exercises and other ways in which these physical limitations (e.g. muscle strength) presently restricting performance can be raised, thus allowing for possible improved performance in the future. In both cases, however, it is the limits of performance which are central

Estimation of Rebound Position in Basketball

AbstractBasketball rebound regions are estimated using a dynamic model for short-, medium-, and long-range direct and bank shots and with previously measured standard deviations of release velocity and angle. The model includes basketball stiffness and damping, and contains flight and ball-contact sub-models. The deterministic simulations, together with random Gaussian probability density functions for release velocity, angle and lateral deviation angle, analyze ball trajectories from different shot positions. The results instruct likely rebounding positions. Angled direct and bank shots from the same release position usually have two high-probability rebound positions, one on the same side as and one on the opposite side from the shooter. The highest probability rebound position is typically in or near the optimal shot path plane for capture. Rebound positions from skilled player's shots are usually more predictable

DIFFERENCES BETWEEN JUMPING AND SOMERSAULTING FROM A DIVING SPRINGBOARD: A SIMULATION STUDY

Maximum-height jumping and jumping for maximizing backward somersault rotations are simulated. The springboard is modeled by a rigid bar with point mass on the tip and a rotational spring on the other hinged end. The planar 4-segment human model is driven by torque actuators at the ankle, knee, and hip. Movement simulation begins from a balanced initial posture and stops at jump takeoff. The objective is to find joint torque activation patterns during board contact so that jump height or the number of backward rotations in flight (determined by takeoff kinematics) is maximized. Kinematic differences between jumps maximizing backward rotations and jumps maximizing height lie mainly in reduced knee angular velocity and consequently bent knees at takeoff. In addition, more significant hip f1exion torque/activation is found in jumps maximizing rotations than that in maximum-height jumps. With reasonable model assumption, this kind of information may be useful for athletic training

Adaptive smartphone-based sensor fusion for estimating competitive rowing kinematic metrics.

Competitive rowing highly values boat position and velocity data for real-time feedback during training, racing and post-training analysis. The ubiquity of smartphones with embedded position (GPS) and motion (accelerometer) sensors motivates their possible use in these tasks. In this paper, we investigate the use of two real-time digital filters to achieve highly accurate yet reasonably priced measurements of boat speed and distance traveled. Both filters combine acceleration and location data to estimate boat distance and speed; the first using a complementary frequency response-based filter technique, the second with a Kalman filter formalism that includes adaptive, real-time estimates of effective accelerometer bias. The estimates of distance and speed from both filters were validated and compared with accurate reference data from a differential GPS system with better than 1 cm precision and a 5 Hz update rate, in experiments using two subjects (an experienced club-level rower and an elite rower) in two different boats on a 300 m course. Compared with single channel (smartphone GPS only) measures of distance and speed, the complementary filter improved the accuracy and precision of boat speed, boat distance traveled, and distance per stroke by 44%, 42%, and 73%, respectively, while the Kalman filter improved the accuracy and precision of boat speed, boat distance traveled, and distance per stroke by 48%, 22%, and 82%, respectively. Both filters demonstrate promise as general purpose methods to substantially improve estimates of important rowing performance metrics

Validation of a laboratory method for evaluating dynamic properties of reconstructed equine racetrack surfaces.

BackgroundRacetrack surface is a risk factor for racehorse injuries and fatalities. Current research indicates that race surface mechanical properties may be influenced by material composition, moisture content, temperature, and maintenance. Race surface mechanical testing in a controlled laboratory setting would allow for objective evaluation of dynamic properties of surface and factors that affect surface behavior.ObjectiveTo develop a method for reconstruction of race surfaces in the laboratory and validate the method by comparison with racetrack measurements of dynamic surface properties.MethodsTrack-testing device (TTD) impact tests were conducted to simulate equine hoof impact on dirt and synthetic race surfaces; tests were performed both in situ (racetrack) and using laboratory reconstructions of harvested surface materials. Clegg Hammer in situ measurements were used to guide surface reconstruction in the laboratory. Dynamic surface properties were compared between in situ and laboratory settings. Relationships between racetrack TTD and Clegg Hammer measurements were analyzed using stepwise multiple linear regression.ResultsMost dynamic surface property setting differences (racetrack-laboratory) were small relative to surface material type differences (dirt-synthetic). Clegg Hammer measurements were more strongly correlated with TTD measurements on the synthetic surface than the dirt surface. On the dirt surface, Clegg Hammer decelerations were negatively correlated with TTD forces.ConclusionsLaboratory reconstruction of racetrack surfaces guided by Clegg Hammer measurements yielded TTD impact measurements similar to in situ values. The negative correlation between TTD and Clegg Hammer measurements confirms the importance of instrument mass when drawing conclusions from testing results. Lighter impact devices may be less appropriate for assessing dynamic surface properties compared to testing equipment designed to simulate hoof impact (TTD).Potential relevanceDynamic impact properties of race surfaces can be evaluated in a laboratory setting, allowing for further study of factors affecting surface behavior under controlled conditions

Effects of Surface Depth and Compaction on Impact Deceleration of Dirt and Synthetic Surface Materials for Equine Racetracks

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A multisegment dynamic model of ski jumping

This paper presents a planar, four-segment, dynamic model for the flight mechanics of a ski jumper. The model consists of skis, legs, torso and head, and anns. Inputs include net joint torques that are used to vary the relative body configurations of the jumper during fiight. The model also relies on aerodynamic data from previous wind tunnel tests that incorporate the effects of varying body configuration and orientation on lift, drag, and pitching moment. A symbolic manipulation program, "Macsyma," is used to derive the equations of motion automatically. Experimental body segment orientation data during the fiight phase arc presented for three ski jumpers which show how jumpers of varying ability differ in flight and demonstrate tlie need for a more complex analytical model than that previously presented in the literature. Simulations are presented that qualitatively match the measured trajectory for a good jumper. The model can be used as a basis for the study of optimal jumper behavior in fiight which maximizes jump distance

Correction: Validation of a Laboratory Method for Evaluating Dynamic Properties of Reconstructed Equine Racetrack Surfaces.

[This corrects the article DOI: 10.1371/journal.pone.0050534.]