Publications

Background/objectives: Para-fencing performance emerges from the interaction of kinematic execution, neuromuscular coordination, and mechanical constraints rather than from execution speed alone. Understanding how these factors combine into distinct performance strategies is essential for individualized assessment and training in adaptive sports. The primary objective of this study was to identify distinct performance strategies in para-fencers by deriving kinematic profiles from inertial measurement unit (IMU) data collected during a standardized offensive task. A secondary objective was to examine whether these strategies could be differentiated based on neuromuscular coordination patterns assessed using surface electromyography (sEMG), along with passive muscle mechanical properties and isometric strength measures.

Methods: Thirty para-fencers performed repeated offensive actions toward a fixed target under controlled laboratory conditions. Upper-limb kinematics and trunk stability were quantified using IMUs, while sEMG was used to assess muscle activation timing, burst characteristics, and agonist–antagonist co-contraction. Passive muscle mechanical properties were evaluated using myotonometry, and isometric strength was measured with a calibrated force device. IMU-derived kinematic features were standardized and analyzed using cluster analysis to identify distinct performance strategies. Between-cluster comparisons were conducted for performance outcomes, neuromuscular variables, muscle mechanical properties, and strength measures.

Results: Three distinct performance strategies were identified. One strategy was characterized by high peak angular velocity, increased trunk oscillation, and greater movement variability, reflecting a fast but variable execution pattern. A second strategy demonstrated smoother movement execution, reduced trunk sway, lower co-contraction levels, and superior accuracy, representing a stable–accurate profile. The third strategy exhibited intermediate characteristics, indicating a balance between execution speed and control. Neuromuscular coordination patterns, passive muscle mechanical properties, and isometric strength measures further differentiated the identified strategies.

Conclusions: Para-fencing performance is organized through distinct movement strategies that reflect differences in kinematic control, neuromuscular coordination, and mechanical constraints rather than speed alone. In the context of this study, movement strategies refer to distinct patterns of movement organization that emerge from the interaction between kinematic execution, neuromuscular coordination, and underlying mechanical properties. These strategies reflect how athletes adapt their motor behavior to task-specific and environmental constraints in order to achieve performance goals. Profiling-based biomechanical approaches provide valuable insight into performance organization and support individualized assessment and training strategies in adaptive sports.

Keywords: inertial measurement units, kinematic profiling, movement strategies, neuromuscular coordination, para-fencing, surface electromyography, trunk stability

This study demonstrated that para-fencing performance during a standardized offensive task is organized around distinct movement strategies rather than a single uniform execution pattern. By integrating IMU-derived kinematic profiling with neuromuscular coordination, passive muscle mechanical properties, and isometric strength measures, three clearly differentiated performance strategies were identified. These strategies reflected meaningful differences in movement smoothness, trunk stability, coordination efficiency, and mechanical constraints, extending beyond simple variations in execution speed.

Athletes exhibiting a stable–accurate strategy achieved superior task accuracy through smoother kinematic execution, reduced trunk sway, earlier muscle activation, and lower agonist–antagonist co-contraction. In contrast, faster strategies were associated with greater movement variability, increased trunk oscillation, and elevated co-contraction, suggesting compensatory control mechanisms under higher mechanical demands. Differences in passive muscle stiffness and strength further contributed to strategy differentiation, highlighting the interaction between neuromuscular control and underlying mechanical properties in shaping movement organization.