Fukuhara Kazunobu, Ida Hirofumi, Ogata Takahiro, Ishii Motonobu, Higuchi Takahiro
Department of Health Promotion Science, Graduate School of Human Health Science, Tokyo Metropolitan University, Minami-Ohsawa, Hachioji, Tokyo, Japan.
Department of Sports and Health Management, Jobu University, Toyazuka-Machi, Isesaki, Gunma, Japan.
PLoS One. 2017 Jul 13;12(7):e0180985. doi: 10.1371/journal.pone.0180985. eCollection 2017.
Recent studies have reported that skilled tennis players are likely to use proximal body information for anticipating the direction of their opponent's forehand shot. However, in these studies, the visual stimuli did not include visual information about the ball. Skilled players may have used proximal information owing to the lack of distal information. To address this issue, we developed a novel methodological approach using computer graphics (CG) images in which the entire body was presented by a combination of point-light display (i.e., poor graphical information, PLD) and polygons (i.e., rich graphical information). Using our novel methodological approach, we examined whether skilled tennis players use proximal body information when anticipating shot directions.
Fifteen skilled tennis players and fifteen novice players tried to anticipate shot directions by observing four CG forehand strokes (ALPOL: all body parts were represented with polygon; RAPLD: racket and arm were represented with PLD; BOPLD: body parts without racket and arm were represented with PLD; and ALPLD: all body parts were represented with PLD). Our intention in creating CG models with such combinations (i.e., RAPLD and BOPLD) was that because of the richer graphical information provided by polygons compared to PLD, the participant's anticipatory judgment would be influenced more by body parts expressed with polygons. The results showed that for skilled players, anticipatory judgment was more accurate when they observed RAPLD than when they observed BOPLD and ALPLD. In contrast, for novice players, there were no differences in the accuracy of anticipatory judgments with the four CG models.
Only skilled players made more accurate anticipatory judgments when body regions were expressed with rich graphical information, and the racket and arm were expressed with poor graphical information. These suggest that skilled players used proximal information to effectively anticipate shot directions.
近期研究报告称,技术娴熟的网球运动员可能会利用身体近端信息来预判对手正手击球的方向。然而,在这些研究中,视觉刺激并未包含关于球的视觉信息。由于缺乏远端信息,技术娴熟的运动员可能使用了近端信息。为解决这一问题,我们开发了一种新颖的方法,利用计算机图形(CG)图像,其中整个身体由点光显示(即图形信息匮乏,PLD)和多边形(即图形信息丰富)组合呈现。使用我们新颖的方法,我们研究了技术娴熟的网球运动员在预判击球方向时是否使用身体近端信息。
15名技术娴熟的网球运动员和15名新手运动员通过观察四个CG正手击球动作(ALPOL:所有身体部位用多边形表示;RAPLD:球拍和手臂用PLD表示;BOPLD:无球拍和手臂的身体部位用PLD表示;以及ALPLD:所有身体部位用PLD表示)来尝试预判击球方向。我们创建具有此类组合(即RAPLD和BOPLD)的CG模型的目的是,由于多边形提供的图形信息比PLD更丰富,参与者的预判判断将更多地受到用多边形表示的身体部位的影响。结果表明,对于技术娴熟的运动员,当他们观察RAPLD时的预判判断比观察BOPLD和ALPLD时更准确。相比之下,对于新手运动员,四种CG模型的预判判断准确性没有差异。
只有技术娴熟的运动员在身体部位用丰富的图形信息表示且球拍和手臂用匮乏的图形信息表示时,做出了更准确的预判判断。这些表明技术娴熟的运动员利用近端信息来有效地预判击球方向。