How Do Humans Learn to Control Unstable Objects? Studies of Model-Based Planning and State-Dependant Force Control

人类如何学习控制不稳定的物体？

• 批准号: 9900684
• 负责人: Ferdinando Mussa-Ivaldi
• 金额: $ 26.12万
• 依托单位: Rehabilitation Institute of Chicago
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-08-01 至 2003-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9900684&HistoricalAwards=false
• 关键词: How; Do; Humans; Learn; Control

9900684Mussa-IvaldiWhile significant progress has been made in our understanding of the mechanisms for executing coordinated arm movements, little is known yet about the sensory-motor processes involved in the skillful manipulation of objects. Common activities such as handling silverware and brushing teeth involve the control of potentially unstable objects. The term 'instability' refers to situations in which small deviations in one's actions can have radical consequences. For example, a small tilt of the hand can spill the contents of a spoon. The proposed research will study human learning and performance of experimental manipulation tasks based on simple unstable objects implemented by means of robotic simulation.Our investigations are aimed at better understanding the interplay between feedback mechanisms and preprogrammed actions in dealing with unstable objects. The work is organized around three specific aims. First, the proposed experiments will test whether internal models are formed during object manipulation, while maintaining the equilibrium of unstable objects. Earlier studies of arm control suggest that the central nervous system makes use of internal models of limb dynamics in order to derive the neuromuscular commands needed to carry out successful reaching movements, but it is not known whether similar strategies are used for object manipulation. Second, when handling an object we receive both visual information and information conveyed by the mechanical interaction between the hand and the object. This information is essential to generate the appropriate corrective actions but it may not be used in the same way as learning progresses. The proposed experiments will test the hypothesis that subjects become less reliant on visual monitoring of the object and more reliant on automatic corrections produced by muscle and reflex mechanics after attaining proficiency in a manipulation task. In a final set of experiments we will seek to determine effective training strategies for learning to handle unstable objects.We expect that this work will advance our understanding of how healthy people handle unstable objects. The achievement of this goal will provide a richer knowledge base for rehabilitation of motor functions lost to stroke and other neurological diseases.

9900684Mussa-Ivaldi 虽然我们对执行协调手臂运动的机制的理解已经取得了重大进展，但我们对巧妙操纵物体所涉及的感觉运动过程知之甚少。 处理银器和刷牙等常见活动涉及对潜在不稳定物体的控制。 “不稳定”一词是指一个人的行为的微小偏差可能会产生根本性后果的情况。 例如，手的轻微倾斜可能会溢出勺子中的内容物。 拟议的研究将研究人类学习和基于通过机器人模拟实现的简单不稳定物体的实验操作任务的表现。我们的研究旨在更好地理解处理不稳定物体时反馈机制和预编程动作之间的相互作用。 这项工作围绕三个具体目标进行。 首先，所提出的实验将测试在物体操纵过程中是否形成内部模型，同时保持不稳定物体的平衡。 早期对手臂控制的研究表明，中枢神经系统利用肢体动力学的内部模型来导出成功进行伸手运动所需的神经肌肉命令，但尚不清楚类似的策略是否用于物体操纵。 其次，当处理物体时，我们既接收到视觉信息，也接收到手与物体之间的机械相互作用所传达的信息。 这些信息对于生成适当的纠正措施至关重要，但其使用方式可能与学习进度不同。 拟议的实验将检验这样的假设：在熟练掌握操作任务后，受试者不再那么依赖于对物体的视觉监控，而是更加依赖于肌肉和反射力学产生的自动校正。在最后一组实验中，我们将寻求确定学习处理不稳定物体的有效训练策略。我们期望这项工作将增进我们对健康人如何处理不稳定物体的理解。 这一目标的实现将为中风和其他神经疾病丧失的运动功能的康复提供更丰富的知识基础。