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全身运动自我辅助协调。

Whole Body Coordination for Self-Assistance in Locomotion.

作者信息

Seyfarth André, Zhao Guoping, Jörntell Henrik

机构信息

Lauflabor Locomotion Laboratory, Institute of Sport Science and Centre for Cognitive Science, Technische Universität Darmstadt, Darmstadt, Germany.

Neural Basis of Sensorimotor Control, Department of Experimental Medical Science, Lund University, Lund, Sweden.

出版信息

Front Neurorobot. 2022 Jun 10;16:883641. doi: 10.3389/fnbot.2022.883641. eCollection 2022.

Abstract

The dynamics of the human body can be described by the accelerations and masses of the different body parts (e.g., legs, arm, trunk). These body parts can exhibit specific coordination patterns with each other. In human walking, we found that the swing leg cooperates with the upper body and the stance leg in different ways (e.g., in-phase and out-of-phase in vertical and horizontal directions, respectively). Such patterns of self-assistance found in human locomotion could be of advantage in robotics design, in the design of any assistive device for patients with movement impairments. It can also shed light on several unexplained infrastructural features of the CNS motor control. Self-assistance means that distributed parts of the body contribute to an overlay of functions that are required to solve the underlying motor task. To draw advantage of self-assisting effects, precise and balanced spatiotemporal patterns of muscle activation are necessary. We show that the necessary neural connectivity infrastructure to achieve such muscle control exists in abundance in the spinocerebellar circuitry. We discuss how these connectivity patterns of the spinal interneurons appear to be present already perinatally but also likely are learned. We also discuss the importance of these insights into whole body locomotion for the successful design of future assistive devices and the sense of control that they could ideally confer to the user.

摘要

人体动力学可以通过不同身体部位(如腿部、手臂、躯干)的加速度和质量来描述。这些身体部位彼此之间可以呈现出特定的协调模式。在人类行走过程中,我们发现摆动腿与上半身和支撑腿以不同方式协作(例如,在垂直和水平方向上分别同相和异相)。在人类运动中发现的这种自我协助模式,在机器人设计以及任何针对运动障碍患者的辅助设备设计中可能具有优势。它还可以揭示中枢神经系统运动控制中一些无法解释的基础特征。自我协助意味着身体的各个分布部分对解决潜在运动任务所需的功能叠加做出贡献。为了利用自我协助效应,精确且平衡的肌肉激活时空模式是必要的。我们表明,在脊髓小脑回路中大量存在实现这种肌肉控制所需的神经连接基础设施。我们讨论了脊髓中间神经元的这些连接模式如何似乎在出生前就已存在,但也可能是后天习得的。我们还讨论了这些关于全身运动的见解对于未来辅助设备成功设计以及它们理想情况下能够赋予用户的控制感的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7433/9211759/31f3ddf333d1/fnbot-16-883641-g0001.jpg

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