When leaping an obstacle, the runner increases the vertical velocity of his/her centre of mass (COM) at takeoff to augment the amplitude and duration of the aerial phase over it. This study analyses the modification of the bouncing mechanism of running when approaching a barrier. The forces exerted by the feet on the ground are measured by a 13-m-long force platform during the four to nine running steps preceding the jump over a 0.45- to 0.85-m-high barrier, at an approaching speed between 9 and 21 km h(-1). The movements of the COM are evaluated by time-integration of the forces and the stiffness of the bouncing system by computer simulation. The running mechanism is modified during the two steps preceding the barrier. During the contact period, two steps before the barrier, the leg-spring stiffness decreases; consequently, the COM is lowered and accelerated forward. Then during the contact period preceding the obstacle, the leg-spring stiffness increases and the COM is raised and accelerated upwards, whereas its forward velocity is reduced. During this phase, the leg-spring acts like a pole, which stores elastic energy and changes the direction of the velocity vector to release this energy in a vertical direction. At high speeds, this storage-release mechanism of elastic energy is sufficient to provide the energy necessary to leap the obstacle. On the contrary, at low speeds, the amount of elastic energy stored and released in the leg-spring is not sufficient to jump over the obstacle and additional positive muscular work must be done.
Athletes use the same mechanisms as non-specialists to cross an obstacle. However, athletes adapt the mechanism of jumping to reduce the loss in the velocity of progression when crossing an obstacle.
Although three-dimensional data capture has become routine, statistical methods that take appropriate advantage of these multivariate data have not been widely developed. Researchers frequently rely on multiple isolated univariate statistical methods in the analysis of a joint's several axes of rotation and their associated motions. This approach reflects an inherent flaw in that it fails to appreciate the unbreakable link among these descriptors. We propose a new analytical perspective. Borrowing from the techniques of geometric morphometrics, data that describe multiple joint axis orientations and the motions about them are converted into a shape, an axis triangle, that is viewable in a three-dimensional space. In this format, multivariate statistical analyses can be conducted using conventional analytical packages. The axis triangle technique represents a significant advance over current analytical approaches in that it provides an encompassing method of appreciating joint rotations, as well as comprehensive consideration of joint function by linking rotational axis orientations with associated motion patterns.
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