INFLUENCE OF RACKET LENGTH ON TENNIS STROKE

The current design of tennis rackets tends toward so-called long body rackets, expected to produce a higher rebound velocity because of the more distally situated hitting point. To study the influence of racket length on the tennis stroke, a standardized computer- model was used, as described by Detlefs and Glitsch (1996). This computer simulation allows a 100% reproducibility with an almost arbitrary time resolution and an independent variation of all input parameters. The experimentally determined geometrical mass distributions of several existing rackets served as input variables for this model. The interesting results are the rebound velocity of the ball and the joint forces of the grip, wrist and elbow. The investigation indicates that the shape of the longer rackets is either obtained by a simple elongation of the grip, keeping the design of the short version, or by creating a completely new design in regard to the mass geometry. As we can see from Fig 1, the gain from a 2% higher rebound velocity increases the loads in the wrist (16%), elbow (17%) and particularly the grip joint (212%), which results in no advantages at acceptable costs for the hobby player. On the other hand, more sophisticatedly designed long body rackets increase ball velocity without producing higher impact loads on the arm. Thus only rackets that are especially designed for a long version yield advantages in tennis performance. An increase in length alone is not a significant feature for the performance of a racket. References: Detlefs, C.; Glitsch, U. (1996). Kinetics of the computer simulated tennis stroke with different rackets. Proc. XIVth Intern. Symposium on Biomechanics in Sports, Funchal, 573-576

MODELING OF ELASTIC RACKET PROPERTIES IN THE DYNAMIC COMPUTER SIMULATION OF TENNIS

INTRODUCTION: Experimental difficulties in tennis research caused by the complexity of the stroke and the short contact phase demand the development of complex computer simulations models which can lead to a better understanding of the tennis stroke. Two different methods are currently in use: (1) The direct dynamics approach, which simulates the dynamic interaction between arm, hand, racket and ball, considering all inertial properties. (2) The finite element method, which analyses the elastic behavior of rackets under static conditions. The aim of this study was to evaluate a complex dynamic simulation model of the tennis stroke, including the elastic racket properties. Therefore a combination of both approaches was tested, by using the results of a finite element analysis as input for a flexible racket model in direct dynamics. METHODS: The racket model was an elastic beam (78 nodes) with parameters determined experimentally. For the dynamic analysis, the model was combined with a multiple rigid body pendulum simulating the players’ arm. By comparing the results of various stroke simulations with different boundary conditions and experimental data, the requirements of a flexible simulation model were worked out. The interesting parameters are acceleration and the vibration frequencies of the racket. RESULTS: First it must be stated that a complex dynamic tennis simulation including all important mechanical properties (inertial and elastic) of the racket is possible (Fig. 1). Second, the analysis of the vibrational parameters indicates that the tennis racket behaves as a freely vibrating body. Only the combination of this racket model with a suitable hand-racket-connection can simulate a real tennis stroke (Fig. 2). Thus, with the described model different previous results could be validated by computer simulation: (1) It is not necessary to fix the handle with large grip forces. (2) Racket tests with a clamped handle lead to incorrect results. CONCLUSIONS: The findings of this evaluation study confirm the possibilities of dynamic tennis simulation. Further investigations concerning the influences of racket properties (e.g., stiffness, node locations) on stroke characteristics are conceivable. [Figures

REARFOOT ANGLE VELOCITIES DURING RUNNING - A COMPARISON BETWEEN OPTOELECTRONIC AND GYROSCOPIC MOTION ANALYSIS

The aim of this study was a verification of a gyroscopic measurement device mounted on the heel counter of a running shoe. For this purpose 15 subjects performed 10 running trials in a laboratory environment. Rearfoot angular velocities from the gyroscope were compared qualitatively and quantitatively to rearfoot angular velocities observed with a 3D motion analysis system (VICON). Based on the qualitative and quantitative analysis the results are very good in the sagittal plane, good in the frontal plane and poor in the transverse plane

Predictive Musculoskeletal Simulation Using Optimal Control: Effects of Added Limb Mass on Energy Cost and Kinematics of Walking and Running

When designing sports equipment, it is often desirable to predict how certain design parameters will affect human performance. In many instances, this requires a consideration of human musculoskeletal mechanics and adaptive neuromuscular control. Current computational methods do not represent these mechanisms, and design optimization typically requires several iterations of prototyping and human testing. This paper introduces a computational method based on musculoskeletal modeling and optimal control, which has the capability to predict the effect of mechanical equipment properties on human performance. The underlying assumption is that users will adapt their neuromuscular control according to an optimality principle, which balances task performance with a minimization of muscular effort. The method was applied to the prediction of metabolic cost and limb kinematics while running and walking with weights attached to the body. A two-dimensional musculoskeletal model was used, with nine kinematic degrees of freedom and 16 muscles. The optimal control problem was solved for two walking speeds and two running speeds, and at each speed, with 200 g and 400 g masses placed at the thigh, knee, shank and foot. The model predicted an increase in energy expenditure that was proportional to the added mass and the effect was largest for a mass placed on the foot. Specifically, the model predicted an energy cost increase of 0.74% for each 100 g mass added to the foot during running at 3.60 m/s. The model also predicted that stride length would increase by several millimetres in the same condition, relative to the model without added mass. These predictions were consistent with previously published human studies. Peak force and activation remained the same in most muscles, but increased by 26% in the hamstrings and by 17% in the rectus femoris for running at 4.27 m/s with 400 g added mass at the foot, suggesting muscle-specific training effects. This work demonstrated that a musculoskeletal model with optimal control can predict the effect of mechanical devices on human performance, and could become a useful tool for design optimization in sports engineering. The theoretical background of predictive simulation also helps explain why human athletes have specific responses when exercising in an altered mechanical environment

Efficient Trajectory Optimization for Curved Running Using a 3D Musculoskeletal Model With Implicit Dynamics

Trajectory optimization with musculoskeletal models can be used to reconstruct measured movements and to predict changes in movements in response to environmental changes. It enables an exhaustive analysis of joint angles, joint moments, ground reaction forces, and muscle forces, among others. However, its application is still limited to simplified problems in two dimensional space or straight motions. The simulation of movements with directional changes, e.g. curved running, requires detailed three dimensional models which lead to a high-dimensional solution space. Weextended a full-body three dimensional musculoskeletal model to be specialized for running with directional changes. Model dynamics were implemented implicitly and trajectory optimization problems were solved with direct collocation to enable efficient computation. Standing, straight running, and curved running were simulated starting from a random initial guess to confirm the capabilities of our model and approach: efficacy, tracking and predictive power. Altogether the simulations required 1 h 17 min and corresponded well to the reference data. The prediction of curved running using straight running as tracking data revealed the necessity of avoiding interpenetration of body segments. In summary, the proposed formulation is able to efficiently predict a new motion task while preserving dynamic consistency. Hence, labor-intensive and thus costly experimental studies could be replaced by simulations for movement analysis and virtual product design

Effect of torsional stiffness on biomechanical variables of the lower extremity during running

Torsion, the relative in-/eversion between forefoot and rearfoot, is a concept that has been incorporated into running shoes for almost 30 years. Studies have shown an influence of footwear torsional stiffness on lower extremity biomechanics during running but results are inconclusive. However, the influence of the torsion axis of the shoe on kinematics and kinetics of running has not been examined. Therefore, the goal was to examine the effect of shoes with a specially designed torsion element on running biomechanics of the lower extremities. Twenty runners performed heel–toe running at 4.0 ms−1 with three shoes and barefoot. All shoes had a torsion element based on a rearfoot and a forefoot element connected by bushings that had a defined rotation axis. The torsional stiffness was altered by modifications made to the torsion element and the surrounding midsole. A force plate and camera system were used to collect kinetics and kinematics. Foot torsion, ankle eversion, ankle and knee moments in the frontal and transverse plane and ground reaction forces were compared between conditions using paired t-tests. The shoe with the lowest torsional stiffness did not result in larger torsion range of motion compared to a stiffer shoe. Ankle eversion decreased with decreasing torsional stiffness while the changes in ankle kinetics were not consistent between the frontal and transverse plane. Torsional stiffness did not have a systematic influence on knee joint kinetics. While shoe torsional stiffness influences foot kinematics significantly, it does not affect lower extremity running biomechanics in a way that would alter the risk of running injuries

Predictive Musculoskeletal Simulation Using Optimal Control: Effects of Added Limb Mass on Energy Cost and Kinematics of Walking and Running

When designing sports equipment, it is often desirable to predict how certain design parameters will affect human performance. In many instances, this requires a consideration of human musculoskeletal mechanics and adaptive neuromuscular control. Current computational methods do not represent these mechanisms, and design optimization typically requires several iterations of prototyping and human testing. This paper introduces a computational method based on musculoskeletal modeling and optimal control, which has the capability to predict the effect of mechanical equipment properties on human performance. The underlying assumption is that users will adapt their neuromuscular control according to an optimality principle, which balances task performance with a minimization of muscular effort. The method was applied to the prediction of metabolic cost and limb kinematics while running and walking with weights attached to the body. A two-dimensional musculoskeletal model was used, with nine kinematic degrees of freedom and 16 muscles. The optimal control problem was solved for two walking speeds and two running speeds, and at each speed, with 200 g and 400 g masses placed at the thigh, knee, shank and foot. The model predicted an increase in energy expenditure that was proportional to the added mass and the effect was largest for a mass placed on the foot. Specifically, the model predicted an energy cost increase of 0.74% for each 100 g mass added to the foot during running at 3.60 m/s. The model also predicted that stride length would increase by several millimetres in the same condition, relative to the model without added mass. These predictions were consistent with previously published human studies. Peak force and activation remained the same in most muscles, but increased by 26% in the hamstrings and by 17% in the rectus femoris for running at 4.27 m/s with 400 g added mass at the foot, suggesting muscle-specific training effects. This work demonstrated that a musculoskeletal model with optimal control can predict the effect of mechanical devices on human performance, and could become a useful tool for design optimization in sports engineering. The theoretical background of predictive simulation also helps explain why human athletes have specific responses when exercising in an altered mechanical environment

Effects of stud design on performance and joint loading during agility tasks including ball handling in soccer

The purpose of this study was to compare three shoe models to serve midfield players. It was hypothesized that different cleat geometries would affect performance and joint loading during midfield specific tasks including ball handling

Optimal Control Simulation Predicts Effects of Midsole Materials on Energy Cost of Running

Testing sports equipment with athletes is costly, time-consuming, hazardous and sometimes impracticable. We propose a method for virtual testing of running shoes and predict how midsoles made of BOOST affect energy cost of running. We contribute a visco-elastic contact model and identified model parameters based on load-displacement measurements. We propose a virtual study using optimal control simulation of musculoskeletal models. The predicted reduction in energy cost of for BOOST in comparison to conventional materials is consistent with experimental studies. This indicates that the proposed method is capable of replacing experimental studies in the future

A thermal foot manikin as a tool for footwear evaluation and development

This study investigated the relationship between thermal perceptions during human wear trials and thermal foot manikin measurements of heat and vapour resistance for five running shoes varying in material and construction. Measurements of thermal/evaporative resistance were performed using a 12-zone sweating thermal-foot manikin. Eleven males performed running trials on five occasions, wearing shoes of same design, differing in materials and construction, to achieve a range of heat/vapour resistances and air permeabilities. Trials in 20°C/60%RH consisted of three phases: 15min rest, 40min running, 15min recovery. In-shoe temperature/humidity were measured at two sites on the left foot. Thermal sensation/wetness perception/thermal comfort were provided for the left foot and four foot regions. Variations in shoe material and construction resulted in differences in thermal and evaporative resistance. These differences were reflected in in-shoe temperature and inshoe absolute humidity assessed during wear trials. At the end of the rest period, thermal sensation was strongly related to thermal insulation (r 2 =0.69, p<0.001). During exercise however, thermal sensation, wetness perception and thermal discomfort were related to both thermal insulation and evaporative resistance. Thermal foot manikins provide a sensitive, effective evaluation of footwear thermal properties, which are also reflective of changes to in-shoe parameters during actual use. This discriminate power may be enhanced using higher, more realistic air-speeds during testing, as well as simulating foot movement. While thermal foot manikins are highly sensitive to design features/attributes of footwear (e.g. ventilation openings, airpermeabilities and coatings), subjective evaluations of footwear do not seem to have the same sensitivity and discriminative power