title: Local versus global optimal sports techniques in a group of athletes.
abstract: Various optimization algorithms have been used to achieve optimal control of sports movements. Nevertheless, no local or global optimization algorithm could be the most effective for solving all optimal control problems. This study aims at comparing local and global optimal solutions in a multistart gradient-based optimization by considering actual repetitive performances of a group of athletes performing a transition move on the uneven bars. Twenty-four trials by eight national-level female gymnasts were recorded using a motion capture system, and then multistart sequential quadratic programming optimizations were performed to obtain global optimal, local optimal and suboptimal solutions. The multistart approach combined with a gradient-based algorithm did not often find the local solution to be the best and proposed several other solutions including global optimal and suboptimal techniques. The qualitative change between actual and optimal techniques provided three directions for training: to increase hip flexion-abduction, to transfer leg and arm angular momentum to the trunk and to straighten hand path to the bar.
authors.affiliation: a Laboratoire d'Automatique de Mécanique et d'Informatique Industrielles et Humaines and Faculté des Sciences du Sport et de l'éducation physique, Université de Lille 2, 9 rue de l'Université , 59790 Ronchin , France.
authors.forename: Aurore
authors.initials: A
authors.lastname: Huchez
authors.forename: Diane
authors.initials: D
authors.lastname: Haering
authors.forename: Patrice
authors.initials: P
authors.lastname: Holvoët
authors.forename: Franck
authors.initials: F
authors.lastname: Barbier
authors.forename: Mickael
authors.initials: M
authors.lastname: Begon
mesh_terms: D000465:Algorithms; D056352:Athletes; D003198:Computer Simulation; D005260:Female; D006173:Gymnastics / Q000502:physiology*; D006801:Humans; D009043:Motor Activity / Q000502:physiology*; D016059:Range of Motion, Articular / Q000502:physiology
keywords: algorithms; gymnastics; optimization; simulation; technique