SIMULATION OF THE FLIGHT DISTANCES OF JAVELINS BASED ON A NEURAL NETWORK APPROACH

INTRODUCTION: The flight distances of javelins are determined by the release parameters as well as by the forces acting on the javelin during flight. The flight phase of the javelin has been under investigation by many researchers using engineering approaches to model the flight phase. The objective is to allow an optimization of the release parameters for maximizing the flight distance. The measurement of release parameters as well as wind influence is not very precise. This means that the models are based on already distorted data. Artificial neural networks (NNs, Haykin 1994) are powerful information processing tools that allow to construct a input-output model of a problem by learning from examples. They are able to generalize , i.e. to produce reasonable outputs for inputs that have not been encountered during learning. NNs handle imprecise data well and could be suitable for modeling the flight distance of javelins as a result of the release parameters. METHODS: Release parameters have been measured using three dimensional film and video analysis. Relevant parameters were determined: the angle of release, the angle of attack (seen from the side), the angle of side attack (seen from behind) as well as the velocity of release. The overall flight was measured as the distance between the throwing line and the athlete’s hand at the point of release plus the distance between the line and the point of touch down of the javelin. Other parameters such as javelin brand, wind speed, etc., were not considered in the model. Multi-Layer-Perceptron Neural Networks (MLPs) were used to construct a model with the release parameters as inputs and the overall distance as output. RESULTS: Several setups were used for the training of the MLPs and 40 sets of release parameters were processed. We used 37 sets for the training of the MLPs and 3 sets were kept for examining the MLPs’ generalization performance (crossvalidation). This was repeated with randomly selected sets for training and crossvalidation. Predictions of the total flight distance using the release parameters were exact up to 5 percent of the overall distance for the cross validation sets. CONCLUSIONS: The MLP simulation of the flight distance is a suitable instrument even though it uses only a small number of parameters. This can be helpful for coaching and provides an alternative to other models. Using more data sets may improve the quality of prediction, and further work will include recording more data sets as well as studies on optimal javelin release parameters. REFERENCES: Haykin, S. (1994). Neural Networks. Englewood Cliffs: Macmillan Publishing Company

Biomechanical analyses of the performance of Paralympians: From foundation to elite level

Biomechanical analysis of sport performance provides an objective method of determining performance of a particular sporting technique. In particular, it aims to add to the understanding of the mechanisms influencing performance, characterization of athletes, and provide insights into injury predisposition. Whilst the performance in sport of able-bodied athletes is well recognised in the literature, less information and understanding is known on the complexity, constraints and demands placed on the body of an individual with a disability. This paper provides a dialogue that outlines scientific issues of performance analysis of multi-level athletes with a disability, including Paralympians. Four integrated themes are explored the first of which focuses on how biomechanics can contribute to the understanding of sport performance in athletes with a disability and how it may be used as an evidence-based tool. This latter point questions the potential for a possible cultural shift led by emergence of user-friendly instruments. The second theme briefly discusses the role of reliability of sport performance and addresses the debate of two-dimensional and three-dimensional analysis. The third theme address key biomechanical parameters and provides guidance to clinicians, and coaches on the approaches adopted using biomechanical/sport performance analysis for an athlete with a disability starting out, to the emerging and elite Paralympian. For completeness of this discourse, the final theme is based on the controversial issues on the role of assisted devices and the inclusion of Paralympians into able-bodied sport is also presented. All combined, this dialogue highlights the intricate relationship between biomechanics and training of individuals with a disability. Furthermore, it illustrates the complexity of modern training of athletes which can only lead to a better appreciation of the performances to be delivered in the London 2012 Paralympic Games

An analysis of the three-dimensional kinetics and kinematics of maximal effort punches among amateur boxers.

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Performance Analysis in Sport on 27-9-18, available online: https://doi.org/10.1080/24748668.2018.1525651The purpose of this study was to quantify the 3D kinetics and kinematics of six punch types among amateur boxers. Fifteen males (age: 24.9 ± 4.2 years; stature: 1.78 ± 0.1 m; body mass: 75.3 ± 13.4 kg; boxing experience: 6.3 ± 2.8 years) performed maximal effort punches against a suspended punch bag during which upper body kinematics were assessed via a 3D motion capture system, and ground reaction forces (GRF) of the lead and rear legs via two force plates. For all variables except elbowjoint angular velocity, analysis revealed significant (P < 0.05) differences between straight, hook and uppercut punches. The lead hook exhibited the greatest peak fist velocity (11.95 ± 1.84 m/s), the jab the shortest delivery time (405 ± 0.15 ms), the rear uppercut the greatest shoulder-joint angular velocity (1069.8 ± 104.5°/s), and the lead uppercut the greatest elbow angular velocity (651.0 ± 357.5°/s). Peak resultant GRF differed significantly (P < 0.05) between rear and lead legs for the jab punch only. Whilst these findings provide novel descriptive data for coaches and boxers, future research should examine if physical and physiological capabilities relate to the key biomechanical qualities associated with maximal punching performance

An analysis of the relationship between the linear hammer speed and the thrower applied forces during the hammer throw for male and female throwers

The purpose of this study was to investigate the relationship between the cable force and linear hammer speed in the hammer throw and to identify how the magnitude and direction of the cable force affects the fluctuations in linear hammer speed. Five male (height: 1.88 ± 0.06 m; body mass: 106.23 ± 4.83 kg) and five female (height: 1.69 ± 0.05 m; body mass: 101.60 ± 20.92 kg) throwers participated and were required to perform 10 throws each. The hammer's linear velocity and the cable force and its tangential component were calculated via hammer head positional data. As expected, a strong correlation was observed between decreases in the linear hammer speed and decreases in the cable force (normalised for hammer weight). A strong correlation was also found to exist between the angle by which the cable force lags the radius of rotation at its maximum (when tangential force is at its most negative) and the size of the decreases in hammer speed. These findings indicate that the most effective way to minimise the effect of the negative tangential force is to reduce the size of the lag angle