Synergistic patterns during steady-state wheelchair propulsion in male wheelchair rugby players with cervical spinal cord injury: influence of functional classification and competitive level.

This cross-sectional study investigated synergistic patterns of wheelchair propulsion in male Wheelchair Rugby (WCR) players and examined how functional classification and competitive level influence propulsive performance. Sixteen male WCR players with cervical spinal cord injuries performed 20 S of steady-state propulsion at 80% of their maximal effort on a roller ergometer. Upper-limb kinematics and surface Electromyography (EMG) were recorded using a motion capture system. To identify synergistic patterns of wheelchair propulsion, a kinematic-muscular synergy analysis was conducted using muscle activation and joint kinematics. EMG and kinematic data were decomposed into three to four synergies, and cluster analysis extracted four distinct synergy patterns with the highest silhouette value (0.611). These patterns were used to classify the propulsion cycle into four functional phases: Preparation, Catch/Pull, Push, and Recovery. The identified synergies and their interactions with muscle recruitment and joint movement patterns suggest classification related modulation of propulsive strategy. In the analysis of propulsive performance, classification scores (0.5-3.0) were associated with temporal propulsion variables, including peak speed, push time, and elbow extension velocity, when controlling for competitive level (marginal R2 = 0.351-0.463, conditional R2 = 0.780-0.819). Accounting for competitive level improved model fit, indicating that the influence of training and experience on propulsive performance is not negligible even within classification categories. Overall, both synergistic patterns and propulsive performance in WCR are associated with functional classification, while propulsive performance also reflects trainability. Explicitly distinguishing the interaction between classification and trainability is essential for evidence-based training design and the refinement of functional classification system.