INTRODUCTION: In springboard diving the diver aims to generate sufficient time in the air and angular momentum for somersault and twist, and travel safely away from the board. Since the linearand angular momentum that the diver possesses in the air are determined by the end of the takeoff phase, it is crucial tounderstand the mechanics of the takeoff in terms of gaining dive height, generating angular momentum and keeping a safedistance. The aim of this study was to develop a computer simulation model in order to investigate springboard diving takeoff techniques in the forward and reverse groups: METHODS: A planar simulation model of a springboard and a diver was developed using the Autolev 3.4TM software package based on Kane`s method of formulating equations of motion [1]. Thediver was represented by an eight-segment linked system comprising the head, upper arm, lower arm, trunk, thigh,shank and a two-segment foot. There were extensor andflexor torque generators acting at the metatarsal-phalangeal, ankle, knee, hip and shoulder joint. The torque produced was the product of an activation level and the maximum torque calculated from a torque / angle / angular velocity function. Each activation level was specified using two quintic functions with six parameters. Input to the model included initial conditions at touchdown obtained using high speed video and activation time histories throughout the simulation. Output of the model comprised time histories of the springboard displacement, the diver`sjoint angle and angular velocity at each joint, body orientation,CM velocity and whole-body angular momentum. The model was customised to an elite female diver so that simulationoutput could be compared with the diver`s own performance.Model parameters including springboard, strength, inertia andvisco-elastic parameters were determined either directly from experiments or indirectly using an angle-driven model. A score was calculated as the average percentage difference injoint angles, orientation, linear momentum, angular momentum, and springboard characteristics. Sixty muscle activation parameters were varied until the best match between simulation and performance was found by minimizing this score using the Simulated Annealing optimisation algorithm [2]. Four dives which required different angular momenta in the forward and reverse groups were selected for this matching process. After satisfactory evaluation, the model was used to optimise takeoff techniques in terms of gaining maximum dive height.
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