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Actively tracking 'passive' stability in a ball bouncing task.

机译:在球弹跳任务中主动跟踪“被动”稳定性。

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This study investigates the control involved in a task where subjects rhythmically bounce a ball with a hand-held racket as regularly as possible to a prescribed amplitude. Stability analyses of a kinematic model of the ball-racket system revealed that dynamically stable solutions exist if the racket hits the ball in its decelerating upward movement phase. Such solutions are resistant to small perturbations obviating explicit error corrections. Previous studies reported that subjects' performance was consistent with this 'passive' stability. However, some 'active' control is needed to attune to this passive stability. The present study investigates this control by confronting subjects with perturbations where stable behavior cannot be maintained solely from passive stability. Six subjects performed rhythmic ball bouncing in a virtual reality set-up with and without perturbations. In the perturbation trials the coefficient of restitution of the ball-racket contact was changed at every fifth contact leading to unexpected ball amplitudes. The perturbations were compensated for within 2-3 bouncing cycles such that ball amplitudes decreased to initial values. Passive stability was reestablished as indicated by negative racket acceleration. Results revealed that an adjustment of the racket period ensured that the impacts occurred at a phase associated with passive stability. These findings were implemented in a model consisting of a neural oscillator that drives a mechanical actuator (forearm holding the racket) to bounce the ball. Following the perturbation, the oscillator's period is adjusted based on the perceived ball velocity after impact. Simulation results reproduced the major aspects of the experimental results.
机译:这项研究调查了一项任务中涉及的控制,在该任务中,受试者用手持球拍有节奏地将球有规律地弹跳到规定的振幅。对球拍系统运动学模型的稳定性分析表明,如果球拍在其减速的向上运动阶段击中球,则存在动态稳定的解决方案。这样的解决方案可以抵抗小的扰动,从而避免了显式的纠错。以前的研究报告说,受试者的表现与这种“被动”稳定性是一致的。但是,需要一些“主动”控制来调和这种被动稳定性。本研究通过使受检者面对摄动,而不能仅靠被动稳定来维持稳定的行为,来研究这种控制。六名受试者在有无扰动的虚拟现实环境中进行有节奏的球弹跳。在摄动试验中,每五次接触球拍接触的恢复系数就会改变,从而导致意外的球振幅。在2-3个弹跳周期内对摄动进行了补偿,以使球的振幅减小到初始值。负球拍加速度表明被动稳定性得到了恢复。结果表明,球拍周期的调整确保了撞击发生在与被动稳定性相关的阶段。这些发现是在由神经振荡器组成的模型中实现的,该神经振荡器驱动机械致动器(握住球拍的前臂)弹跳球。扰动之后,根据感知到的撞击后的球速来调整振荡器的周期。仿真结果重现了实验结果的主要方面。

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