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相关概念视频

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Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
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A fixed action pattern (FAP) is a specific, hard-wired sequence of behaviors that occurs in response to an external stimulus, called a sign stimulus. The behavior is “fixed” because it is essentially unchangeable—proceeding similarly across individuals of a species every time it occurs.
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The nervous system consists of complex motor neuron circuits, including upper motor neurons originating from the cerebral cortex and lower motor neurons starting in the spinal cord, coordinating both voluntary and involuntary movements. Among these, somatic motor neurons activate skeletal muscles and are classified into alpha, beta, and gamma types. Alpha neurons are vital for voluntary movement coordination, while gamma neurons adjust muscle spindle sensitivity, and the function of beta...
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Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
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在行走过程中自动识别下肢神经肌肉激活模式,使用织可穿戴多传感器系统.

Federica Amitrano1, Armando Coccia1, Federico Colelli Riano1

  • 1Movement Analysis and Robotics Laboratory (MARLab), Istituti Clinici Scientifici Maugeri IRCCS, Telese Terme Institute, 82037 Benevento, Italy.

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概括

这项研究开发了一种舒适的可穿戴系统,使用表面肌电图 (sEMG) 和压力内来监测步行期间的肌肉激活. 该系统有效地捕获了健康成年人的前和胃后活动模式.

关键词:
电子织品 电子织品步态分析 步态分析肌肉激活模式 肌肉激活模式神经运动康复疗法 神经运动康复脚部压力传感器表面电肌图 (sEMG) 是一种表面电肌图.使用织品为基础的电极.可穿戴式健康监测设备可以穿戴的传感器.

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科学领域:

  • 生物医学工程 生物医学工程
  • 运动学 运动学
  • 可穿戴技术可穿戴技术

背景情况:

  • 穿戴式传感器对于评估日常活动中的神经肌肉功能至关重要.
  • 在临床评估中,准确监测步行过程中的肌肉激活是非常重要的.

研究的目的:

  • 介绍和评估一款多传感器可穿戴系统,用于在走路时监测前 (TA) 和胃半后 (GL) 肌肉激活.
  • 评估整合表面肌电图 (sEMG) 和足部压力传感的可行性和有效性.

主要方法:

  • 开发了一个系统,结合了基于织品的sEMG袖子和压力传感内底.
  • 收集了11名健康成年人在地面上行走时的同步sEMG和脚部压力数据.
  • 利用专门的算法来检测跨行走周期的肌肉激活间隔.

主要成果:

  • 可穿戴系统舒适,并提供稳定的录音.
  • 每个步行周期检测到1-4个肌肉激活爆发,在终端摆动中具有一致的TA活动,在中至终端姿势中具有GL活动.
  • 观察到肌肉激活模式的个体间和个体内变化,与生理步态调节保持一致.

结论:

  • 多传感器可穿戴系统可用于描述行走期间的肌肉激活.
  • 该系统的舒适性,信号质量和易于集成支持其用于临床步态分析和远程监控.
  • 未来的研究将专注于系统优化和在不同人群中的验证.