Regulation of pendulum length as a control mechanism in performing the backward giant circle in gymnastics

Automatic recognition and scoring of olympic rhythmic gymnastic movements

We describe a conceptually simple algorithm for assigning judgement scores to rhythmic gymnastic movements, which could improve scoring objectivity and reduce judgemental bias during competitions. Our method, implemented as a real-time computer vision software, takes a video shot or a live performance video stream as input and extracts detailed velocity field information from body movements, transforming them into specialized spatio-temporal image templates. The collection of such images over time, when projected into a velocity covariance eigenspace, trace out unique but similar trajectories for a particular gymnastic movement type. By comparing separate executions of the same atomic gymnastic routine, our method assigns a quality judgement score that is related to the distance between the respective spatio-temporal trajectories. For several standard gymnastic movements, the method accurately assigns scores that are comparable to those assigned by expert judges. We also describe our rhythmic gymnastic video shot database, which we have made freely available to the human movement research community. The database can be obtained at http://www.milegroup.net/apps/gymdb/.

Between-subject variability of muscle synergies during a complex motor skill

The purpose of the present study was to determine whether subjects who have learned a complex motor skill exhibit similar neuromuscular control strategies. We studied a population of experienced gymnasts during backward giant swings on the high bar. This cyclic movement is interesting because it requires learning, as untrained subjects are unable to perform this task. Nine gymnasts were tested. Both kinematics and electromyographic (EMG) patterns of 12 upper-limb and trunk muscles were recorded. Muscle synergies were extracted by non-negative matrix factorization (NMF), providing two components: muscle synergy vectors and synergy activation coefficients. First, the coefficient of correlation (r) and circular cross-correlation (r(max)) were calculated to assess similarities in the mechanical patterns, EMG patterns, and muscle synergies between gymnasts. We performed a further analysis to verify that the muscle synergies (in terms of muscle synergy vectors or synergy activation coefficients) extracted for one gymnast accounted for the EMG patterns of the other gymnasts. Three muscle synergies explained 89.9 ± 2.0% of the variance accounted for (VAF). The coefficients of correlation of the muscle synergy vectors among the participants were 0.83 ± 0.08, 0.86 ± 0.09, and 0.66 ± 0.28 for synergy #1, #2, and #3, respectively. By keeping the muscle synergy vectors constant, we obtained an averaged VAF across all pairwise comparisons of 79 ± 4%. For the synergy activation coefficients, r(max)-values were 0.96 ± 0.03, 0.92 ± 0.03, and 0.95 ± 0.03, for synergy #1, #2, and #3, respectively. By keeping the synergy activation coefficients constant, we obtained an averaged VAF across all pairwise comparisons of 72 ± 5%. Although variability was found (especially for synergy #3), the gymnasts exhibited gross similar neuromuscular strategies when performing backward giant swings. This confirms that the muscle synergies are consistent across participants, even during a skilled motor task that requires learning.

On the organizing role of nonmuscular forces during performance of a giant circle in gymnastics

Five elite gymnasts performed giant circles on the high bar under different conditions of loading (without and with 6-kg loads attached to the shoulders, waist or ankles). Comparing the gymnasts' kinematic pattern of movement with that of a triple-pendulum moving under the sole influence of nonmuscular forces revealed qualitative similarities, including the adoption of an arched position during the downswing and a piked position during the upswing. The structuring role of nonmuscular forces in the organization of movement was further reinforced by the results of an inverse dynamics analysis, assessing the contributions of gravitational, inertial and muscular components to the net joint torques. Adding loads at the level of the shoulders, waist or ankles systematically influenced movement kinematics and net joint torques. However, with the loads attached at the level of the shoulders or waist, the load-induced changes in gravitational and inertial torques provided the required increase in net joint torque, thereby allowing the muscular torques to remain unchanged. With the loads attached at the level of the ankles, this was no longer the case and the gymnasts increased the muscular torques at the shoulder and hip joints. Together, these results demonstrate that expert gymnasts skillfully exploit the operative nonmuscular forces, employing muscle force only in the capacity of complementary forces needed to perform the task.