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相关概念视频

Feedback control systems01:26

Feedback control systems

767
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
767
Cross-bridge Cycle01:26

Cross-bridge Cycle

124.3K
As muscle contracts, the overlap between the thin and thick filaments increases, decreasing the length of the sarcomere—the contractile unit of the muscle—using energy in the form of ATP. At the molecular level, this is a cyclic, multistep process that involves binding and hydrolysis of ATP, and movement of actin by myosin.
124.3K
Effects of feedback01:24

Effects of feedback

1.1K
Feedback in control systems plays a critical role in shaping various operational parameters, extending beyond simple error reduction to influence stability, bandwidth, gain, impedance, and sensitivity. Understanding these effects requires examining a basic feedback system characterized by defined input, output, error, and feedback signals.
Feedback significantly modifies the gain of a control system. The gain of a system without feedback is altered by a factor of one plus GH, where G represents...
1.1K
Direct Motor Pathways01:11

Direct Motor Pathways

5.1K
The direct motor pathways, also known as the pyramidal tracts, are a group of neural pathways that originate in the brain and descend through the spinal cord. They control the voluntary movement of the body. There are two major direct motor pathways: the corticospinal and the corticobulbar tracts.
The corticospinal tract is responsible for the voluntary movement of the limbs and trunk. It originates in the cerebral cortex of the brain and descends through the cerebrum's internal capsule and...
5.1K
Muscle Stimulation Frequency01:22

Muscle Stimulation Frequency

5.0K
The contraction strength of muscles is regulated by motor neurons, which modulate the frequency of action potentials dispatched to the motor units based on the body's requirements. This process of varying the muscle stimulation frequency allows muscles to contract with a force that is precisely tailored to the needs of the moment, whether lifting a feather or a heavy box.
Wave summation
At low firing rates, motor neurons induce individual twitch contractions in muscle fibers. These twitches...
5.0K
Positive and Negative Feedback Loops01:18

Positive and Negative Feedback Loops

26.0K
Animal organs and organ systems constantly adjust to internal and external changes through a process called homeostasis ("steady state"). Examples of these changes include regulation of the level of glucose or calcium in the blood or internal responses to external temperatures. Homeostasis requires  maintaining an internal dynamic equilibrium:
26.0K

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相关实验视频

Updated: Mar 17, 2026

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
10:52

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Published on: April 13, 2016

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协同反控制预测了跨越多个周期的步行.

Spencer Williams, Geng Li, B J Fregly

    bioRxiv : the preprint server for biology
    |March 16, 2026
    PubMed
    概括

    这项研究为中风患者开发了一种个性化的神经肌肉骨模型,发现显著水平的前控制对于准确模拟行走动态至关重要. 足够的数据匹配对于预测患者特定的运动也至关重要.

    科学领域:

    • 生物力学 生物力学
    • 神经科学是一个神经科学.
    • 计算建模计算建模

    背景情况:

    • 神经反对于运动控制至关重要,但神经障碍会破坏这一过程.
    • 现有的计算模型往往缺乏个性化,限制了它们对运动障碍的临床应用.

    研究的目的:

    • 开发和评估一种基于协同作用的新型前 (FF) +反 (FB) 神经肌肉骨模型.
    • 使用个性化的行走数据,为个人中风后创建一个特定患者的模型.

    主要方法:

    • 开发了一个个性化的3D神经肌肉骨行走模型,使用来自中风后受试者的实验数据.
    • 计算了名义FF协同控制并缩放了它们,装配了FB协同控制来重建肌肉激活和关节时刻.
    • 在使用特定主题数据的预测模拟中评估了六个FF+FB模型.

    主要成果:

    • 具有100%前控制的模型最准确地复制了实验步行周期.
    • 更高水平的前控制 (75-125%) 是必要的,以产生近周期性行走动作与一致的初始条件.
    • 较低的前进料水平需要在周期运动的初始条件上有很大差异.

    结论:

    • 走路的预测模拟需要一个前进控制的最低门.

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  • 准确预测动态一致的,患者特异性的运动需要足够的装配数据和前控制.