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Multifractality in postural sway supports quiet eye training in aiming tasks: A study of golf putting

机译:姿势摇摆中的多分行性支持瞄准任务的安静眼睛训练:高尔夫推杆的研究

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The ?quiet eye? (QE) approach to visually-guided aiming behavior invests fully in perceptual information?s potential to organize coordinated action. Sports psychologists refer to QE as the stillness of the eyes during aiming tasks and increasingly into self-and externally-paced tasks. Amidst the ?noisy? fluctuations of the athlete?s body, quiet eyes might leave fewer saccadic interruptions to the coupling between postural sway and optic flow. Postural sway exhibits fluctuations whose multifractal structure serves as a robust predictor of visual and haptic perceptual responses. Postural sway generates optic flow centered on an individual?s eye height. We predicted that perturbing the eye height by attaching wooden blocks below the feet would perturb the putting more so in QE-trained participants than participants trained technically. We also predicted that QE?s efficacy and responses to perturbation would depend on multifractality in postural sway. Specifically, we predicted that less multifractality would predict more adaptive responses to the perturbation and higher putting accuracy. Results showed that lower multifractality led to more accurate putts, and the perturbation of eye height led to less accurate putts, particularly for QE-trained participants. Models of radial error (i.e., the distance between the ball?s final position and the hole) indicated that lower estimates of multifractality due to nonlinearity coincided with a more adaptive response to the perturbation. These results suggest that reduced multifractality may act in a context-sensitive manner to restrain motoric degrees of freedom to achieve the task goal.
机译:这个安静的眼睛?(QE)视觉引导瞄准行为的方法完全投资于感知信息?组织协调行动的潜力。运动心理学家将QE称为瞄准任务期间眼睛的静止,并越来越多地进入自我和外部节奏的任务。在黑暗中?吵闹的运动员的波动?在人体内,安静的眼睛可能会对姿势摆动和光流之间的耦合造成更少的扫视干扰。姿势摆动表现出波动,其多重分形结构可作为视觉和触觉感知反应的稳健预测因子。姿势摆动产生以个人为中心的光流?s的眼睛高度。我们预测,通过在脚底下方安装木块来干扰眼睛高度,会使QE培训的参与者比接受技术培训的参与者更容易受到干扰。我们还预测量化宽松?s的功效和对扰动的反应取决于姿势摆动的多重分形。具体来说,我们预测,较低的多重分形将预测对扰动的更适应性反应和更高的推杆精度。结果表明,较低的多重分形导致了更准确的推杆,而眼睛高度的扰动导致了更不准确的推杆,尤其是对于受过QE训练的参与者。径向误差模型(即,球的最终位置与球洞之间的距离)表明,由于非线性导致的多重分形的较低估计值与对扰动的更自适应响应一致。这些结果表明,减少的多重分形可能会以上下文敏感的方式抑制运动自由度以实现任务目标。

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