Quantitative Relation between Server Motion and Receiver Anticipation in Tennis: Implications of Responses to Computer-Simulated Motions

Abstract

The purpose of this study was to determine the quantitative relationships between the server's motion and the receiver's anticipation using a computer graphic animation of tennis serves. The test motions were determined by capturing the motion of a model player and estimating the computational perturbations caused by modulating the rotation of the player's elbow and forearm joints. Eight experienced and eight novice players rated their anticipation of the speed, direction, and spin of the ball on a visual analogue scale. The experienced players significantly altered some of their anticipatory judgment depending on the percentage of both the forearm and elbow modulations, while the novice players indicated no significant changes. Multiple regression analyses, including that of the racket's kinematic parameters immediately before racket-ball impact as independent variables, showed that the experienced players demonstrated a higher coefficient of determination than the novice players in their anticipatory judgment of the ball direction. The results have implications on the understanding of the functional relation between a player's motion and the opponent's anticipatory judgment during real play.

Recognition of Tennis Serve Performed by a Digital Player: Comparison among Polygon, Shadow, and Stick-Figure Models

“…Several studies have introduced techniques for injecting modified local motions into an original gross motion, i.e., perturbation of motion. These have included spatial exaggeration [27], dynamic simulation and noise addition [28], decomposition by principal component analysis [16], [29], and the modulation of joint angular velocity [30], [31]. For instance, three tennis serves (flat, slice, and topspin) were spatially exaggerated and displayed using a polygon CG model, and the serve type was more accurately identified as the level of exaggeration increased [27].…”

“…The technique perturbs the upper arm motion by computationally modulating the joint rotation speed (joint angular velocity) of the original motion, while the modified motions yields no violation of the anatomical constraint of the joint degree-of-freedom [30]. It has been shown that tennis players are sensitive to the change of the opponent's racket-arm motion simulated by this perturbation technique [31].…”

Computer-Simulated Display to Advance the Understanding of Perceptual Motor Skills

“…Spatial exaggeration is also a perturbation technique and a previous study using this method in the study of tennis serve motion using a polygon humanoid model showed that a higher exaggeration rate increased the accuracy of serve type categorization [45]. Another study manipulated the tennis serve motion while maintaining the anatomical constraints on joint rotation and found that the anticipation of the ball direction was monotonically shifted based on the perturbation rate of the forearm pronation/supination and elbow extension/flexion of the polygon server [46,47]. Motion synthesis is useful for composing test motions.…”

Can Slow-Motion Footage of Forehand Strokes Be Used to Immediately Improve Anticipatory Judgments in Tennis?

“…The forehand stroke in tennis is a rapid movement; therefore, the use of slow-motion footage should lead to the activation of the AON. Considering that skilled anticipatory judgments are underpinned by the detection of key kinematic cues from an opponent’s movements ( Jones and Miles, 1978 ; Shim et al, 2005 ; Abernethy and Zawi, 2007 ; Jackson and Mogan, 2007 ; Williams et al, 2009 ; Ida et al, 2011a , b ; Fukuhara et al, 2017 ), the prolonged time afforded to detect key kinematic cues from an opponent’s movements would lead to better anticipatory performance.…”