Predictability and Robustness in the Manipulation of Dynamically Complex Objects.
Predictability and Robustness in the Manipulation of Dynamically Complex Objects.
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DOI：
10.1007/978-3-319-47313-0_4
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发表时间：
2016
影响因子：
--
通讯作者：
Hasson CJ
中科院分区：
文献类型：
--
作者：
Sternad D;Hasson CJ
操纵复杂的物体和工具是许多日常生活活动的标志，但人类神经运动控制系统如何与这些物体相互作用尚不清楚。即使是看似简单的任务--运送一杯咖啡而不洒出来--也会产生复杂的相互作用力，人类需要进行补偿。基于内部模型用非线性流体动力学预测驱动不足物体的行为似乎令人望而生畏。因此，这项研究测试了一种假设，即人类学习的策略使互动可以预测，并对物体动力学的神经表征中的不准确具有健壮性。移动一杯咖啡的任务是用一个手推车和摆系统模拟的，该系统在虚拟环境中渲染，受试者使用机器人操作手与一个虚拟的杯子互动，杯子里有一个滚动的球。为了深入了解人类的控制策略，我们将可预测性和稳健性应用于量化的理论评估。可预测性用作用力和物体动力学之间的互信息来量化，稳健性用远离故障的能量裕度来量化。本文回顾了三项研究，这三项研究展示了受试者如何通过练习发展出可预测和健壮的运动策略。自由运动常用的替代标准，如最大化平稳性和最小化作用力，没有考虑到观察到的数据。由于许多神经疾病患者的手动灵活性受到影响，实验范式及其分析是一个有希望的平台，可以深入了解神经疾病，如肌张力障碍和多发性硬化症，以及健康老龄化。
Manipulation of complex objects and tools is a hallmark of many activities of daily living, but how the human neuromotor control system interacts with such objects is not well understood. Even the seemingly simple task of transporting a cup of coffee without spilling creates complex interaction forces that humans need to compensate for. Predicting the behavior of an underactuated object with nonlinear fluid dynamics based on an internal model appears daunting. Hence, this research tests the hypothesis that humans learn strategies that make interactions predictable and robust to inaccuracies in neural representations of object dynamics. The task of moving a cup of coffee is modeled with a cart-and-pendulum system that is rendered in a virtual environment, where subjects interact with a virtual cup with a rolling ball inside using a robotic manipulandum. To gain insight into human control strategies, we operationalize predictability and robustness to permit quantitative theory-based assessment. Predictability is quantified by the mutual information between the applied force and the object dynamics; robustness is quantified by the energy margin away from failure. Three studies are reviewed that show how with practice subjects develop movement strategies that are predictable and robust. Alternative criteria, common for free movement, such as maximization of smoothness and minimization of force, do not account for the observed data. As manual dexterity is compromised in many individuals with neurological disorders, the experimental paradigm and its analyses are a promising platform to gain insights into neurological diseases, such as dystonia and multiple sclerosis, as well as healthy aging.
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