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不稳定动力学的稳定化策略。

Stabilization strategies for unstable dynamics.

机构信息

Department of Biomedical Engineering, Northwestern University, Chicago, Illinois, United States of America.

出版信息

PLoS One. 2012;7(1):e30301. doi: 10.1371/journal.pone.0030301. Epub 2012 Jan 18.

Abstract

BACKGROUND

When humans are faced with an unstable task, two different stabilization mechanisms are possible: a high-stiffness strategy, based on the inherent elastic properties of muscles/tools/manipulated objects, or a low-stiffness strategy, based on an explicit positional feedback mechanism. Specific constraints related to the dynamics of the task and/or the neuromuscular system often force people to adopt one of these two strategies.

METHODOLOGY/FINDINGS: This experiment was designed such that subjects could achieve stability using either strategy, with a marked difference in terms of effort and control requirements between the two strategies. The task was to balance a virtual mass in an unstable environment via two elastic linkages that connected the mass to each hand. The dynamics of the mass under the influence of the unstable force field and the forces applied through the linkages were simulated using a bimanual, planar robot. The two linkages were non-linear, with a stiffness that increased with the amount of stretch. The mass could be stabilized by stretching the linkages to achieve a stiffness that was greater than the instability coefficient of the unstable field (high-stiffness), or by balancing the mass with sequences of small force impulses (low-stiffness). The results showed that 62% of the subjects quickly adopted the high-stiffness strategy, with stiffness ellipses that were aligned along the direction of instability. The remaining subjects applied the low-stiffness strategy, with no clear preference for the orientation of the stiffness ellipse.

CONCLUSIONS

The choice of a strategy was based on the bimanual coordination of the hands: high-stiffness subjects achieved stability quickly by separating the hands to stretch the linkages, while the low-stiffness subjects kept the hands close together and took longer to achieve stability but with lower effort. We suggest that the existence of multiple solutions leads to different types of skilled behavior in unstable environments.

摘要

背景

当人类面临不稳定的任务时,可能有两种不同的稳定机制:一种是基于肌肉/工具/被操作物体固有弹性特性的高刚度策略,另一种是基于明确的位置反馈机制的低刚度策略。与任务和/或神经肌肉系统动力学相关的特定约束条件通常迫使人们采用这两种策略之一。

方法/发现:本实验的设计使得受试者可以使用这两种策略中的任何一种来实现稳定性,这两种策略在努力和控制要求方面有明显的区别。任务是通过连接到每个手的两个弹性连杆在不稳定环境中平衡一个虚拟质量。质量在不稳定力场的影响下以及通过连杆施加的力的动力学使用双手平面机器人进行模拟。两个连杆是非线性的,其刚度随拉伸量增加而增加。质量可以通过拉伸连杆来实现刚度大于不稳定场的不稳定性系数(高刚度)来稳定,或者通过用小力脉冲序列平衡质量(低刚度)来稳定。结果表明,62%的受试者很快采用了高刚度策略,其刚度椭圆沿不稳定性方向对齐。其余受试者采用低刚度策略,其刚度椭圆的取向没有明显偏好。

结论

策略的选择基于双手的双手协调:高刚度受试者通过分离双手来拉伸连杆快速实现稳定性,而低刚度受试者则将手靠近在一起,花费更长时间实现稳定性,但努力较小。我们认为,存在多种解决方案导致在不稳定环境中出现不同类型的熟练行为。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d61/3261184/f99cc1b2f027/pone.0030301.g001.jpg

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