Cyclic relationship of mechanical likelihood: Coupling perception-action states in extended haptic accuracy

The present study investigates the dynamic nature of haptic accuracy in racket sports, specifically focusing on self-produced movements in participants with different skill levels (novice vs. expert). The study examines performance accuracy using indicators such as absolute error size and the coefficient of restitution as measures of haptic accuracy. To collect and analyze the data, custom-made devices, including shock and vibration sensors and Qualisys Track Manager, were used. The results indicate that skilled participants demonstrated higher accuracy, reflected by smaller absolute error sizes, and exhibited reduced variability in impulse vibration during self-produced movements. Moreover, employing maximum likelihood estimation and differential equations, we reveal cyclic relationships among these mechanical features. These findings provide valuable insights into perception-action coupling within different haptic skill levels, contributing to a comprehensive understanding of expertise in racket sports. By shedding light on the intricate relationship between haptic accuracy and performance, this research offers a valuable framework for studying perception-action coupling in racket sports and can potentially guide future investigations.