title: Effect of swimming velocity on arm coordination in the front crawl: a dynamic analysis.
abstract: We examined the preferred mode of arm coordination in 14 elite male front-crawl swimmers. Each swimmer performed eight successive swim trials in which target velocity increased from the swimmer's usual 3000-m velocity to his maximal velocity. Actual swim velocity, stroke rate, stroke length and the different arm stroke phases were then calculated from video analysis. Arm coordination was quantified by an index of coordination based on the lag time between the propulsive phases of each arm. The index expressed the three coordination modes in the front crawl: opposition, catch-up and superposition. First, in line with the dynamic approach to movement coordination, the index of coordination could be considered as an order parameter that qualitatively captured arm coordination. Second, two coordination modes were observed: a catch-up pattern (index of coordination= -8.43%) consisting of a lag time between the propulsive phases of each arm, and a relative opposition pattern (index of coordination= 0.89%) in which the propulsive phase of one arm ended when the propulsive phase of the other arm began. An abrupt change in the coordination pattern occurred at the critical velocity of 1.8 m. s(-1), which corresponded to the 100-m pace: the swimmers switched from catch-up to relative opposition. This change in coordination resulted in a reorganization of the arm phases: the duration of the entry and catch phase decreased, while the duration of the pull and push phases increased in relation to the whole stroke. Third, these changes were coupled to increased stroke rate and decreased stroke length, indicating that stroke rate, stroke length, the stroke rate/stroke length ratio, as well as velocity, could be considered as control parameters. The control parameters can be manipulated to facilitate the emergence of specific coordination modes, which is highly relevant to training and learning. By adjusting the control and order parameters within the context of a specific race distance, both coach and swimmer will be able to detect the best adapted pattern for a given race pace and follow how arm coordination changes over the course of training.
authors.affiliation: CETAPS Laboratory, Faculty of Sports Sciences, University of Rouen, Mont Saint Aignan, France. l.seifert@libertysurf.fr
authors.forename: L
authors.initials: L
authors.lastname: Seifert
authors.forename: D
authors.initials: D
authors.lastname: Chollet
authors.forename: B G
authors.initials: BG
authors.lastname: Bardy
mesh_terms: D000328:Adult; D001132:Arm / Q000502:physiology*; D001696:Biomechanical Phenomena; D005080:Exercise Test; D006801:Humans; D008297:Male; D009048:Motor Skills / Q000502:physiology*; D009068:Movement / Q000502:physiology*; D009119:Muscle Contraction / Q000502:physiology; D009126:Muscle Relaxation / Q000502:physiology; D005082:Physical Exertion / Q000502:physiology*; D013550:Swimming / Q000502:physiology*; D014741:Video Recording