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相关概念视频

Motor Unit Stimulation01:20

Motor Unit Stimulation

When the neuron of a motor unit fires an action potential, it triggers a series of events, leading to a twitch contraction in the muscle fibers. The process of excitation-contraction coupling is crucial in relaying the action potential to the muscle fibers.
The latent period of contraction marks the onset of excitation-contraction coupling, when the action potential propagates across the sarcolemma, preparing the muscle fibers for contraction. As the fibers enter the contraction phase, the...
Hierarchy of Motor Control01:18

Hierarchy of Motor Control

The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
Neural Control of Respiration01:18

Neural Control of Respiration

The neural regulation of respiration is a meticulously coordinated process primarily controlled by the respiratory centers located within the brainstem. These centers, composed of specialized neurons, transmit nerve impulses that control the contraction and relaxation of our respiratory muscles.
Respiratory Centers in the Brainstem
Two primary areas comprise the respiratory center: the medullary respiratory center in the medulla oblongata and the pontine respiratory group in the pons. The...

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相关实验视频

Updated: Jun 22, 2026

Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis
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Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis

Published on: July 22, 2014

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一个深度学习框架,用于端到端控制动力假肢.

Christoph P O Nuesslein1, Aaron J Young1

  • 1Institute for Robotics and Intelligent Machines and the Department of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332 USA.

IEEE robotics and automation letters
|February 27, 2025
PubMed
概括

深度学习模型可以控制活跃的下肢假肢,消除手动调. 一个时卷积网络 (TCN) 在各种运动模式中展示了对跨截肢者的用户独立控制.

科学领域:

  • 生物医学工程 生物医学工程
  • 机器人技术 机器人技术 机器人技术
  • 人工智能的人工智能

背景情况:

  • 活动下肢假肢的传统控制依赖于手工调节的参数和复杂的状态机器.
  • 深度学习为端到端控制提供了一种新的方法,有可能简化假肢操作并提高适应性.

研究的目的:

  • 调查深度学习模型的有效性,特别是时卷积网络 (TCN),用于控制开源驱动的膝关节假肢 (OSL).
  • 评估模型能够产生独立于用户和模式的联合扭矩的能力,消除了对传统控制策略的需求.

主要方法:

  • 采集了来自12名腿部截肢者的传感器数据和指挥扭矩,使用OSL跨越五种运动模式.
  • 训练了一台TCN来估计立场阶段并产生膝盖和脚扭矩,将性能与专家调节的有限状态机器控制器进行比较.
  • 使用根平均平方误差 (RMSE) 评估模型性能,并分析适应步行速度和斜率变化的情况.

主要成果:

  • TCN实现了模式和用户独立的膝盖和脚扭矩控制,其RMSE分别为0.154 ± 0.06和0.106 ± 0.06Nm/kg.
  • 对模式特定数据的培训显著降低了楼梯下降的RMSE.
  • 经过多次测试,TCN证明了适应步行速度和坡度的变化的能力.
关键词:
假肢 假肢是一种假肢.深度学习是一种深度学习.终端到终端的控制控制扭矩估计的时间.

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相关实验视频

Last Updated: Jun 22, 2026

Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis
11:16

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Published on: July 22, 2014

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Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

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结论:

  • 深度学习,特别是TCN,可以有效地取代下肢假体控制中的启发式状态机器和模式分类.
  • 这种方法有可能显著减少或消除人工假肢辅助调整的需要,提高用户体验和性能.