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相关概念视频

Tactile and Chemical Senses01:27

Tactile and Chemical Senses

Tactile senses encompass touch, temperature, and pain, each mediated by specific receptors. Touch receptors detect mechanical energy or pressure against the skin. Sensory fibers from these receptors enter the spinal cord and relay information to the brain stem. Here, most fibers cross over to the opposite side of the brain. The touch information then moves to the thalamus, which projects a map of the body's surface onto the somatosensory areas of the parietal lobes in the cerebral cortex. This...

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基于尖的神经形态硬件用于动态触觉感知,具有自动供电的机械感应器阵列.

Sang-Won Lee1, Seong-Yun Yun1, Joon-Kyu Han2

  • 1School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
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概括

这项研究介绍了一种自动供电的机械感应器阵列,使用 triboelectric nanogenerators (TENGs) 和 biristors 来进行触摸手势识别. 该系统在使用尖端神经网络 (SNN) 进行手势分类时实现了92.5%的准确性.

关键词:
人工机械感受器阵列.一个双晶体管动态手势识别 动态手势识别尖端神经网络 (SNN) 是一个神经网络.triboelectric纳米发电机 (TENG) 的使用

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科学领域:

  • 材料科学与工程 材料科学与工程
  • 神经系统启发的计算
  • 传感器和执行器

背景情况:

  • 开发自动供电的触觉传感系统对于先进的机器人技术和物联网 (IoT) 至关重要.
  • 现有的触觉传感器通常需要外部电源,这限制了它们在低功耗设备中的适用性.
  • 尖端神经网络 (SNN) 为复杂的模式识别任务提供节能计算.

研究的目的:

  • 为了展示一个自动供电的机械感应器阵列,用于动态触摸手势识别.
  • 集成用于触摸感应的 triboelectric 纳米发电机 (TENG) 和用于尖端编码的 biristor.
  • 为了验证系统的性能,使用尖端神经网络 (SNN) 来进行手势分类.

主要方法:

  • 一个机械感应器阵列的制造,包括四个TENG-biristor电池.
  • 使用TENG来感知外部触摸力并将其转换为电信号.
  • 采用比里斯托来编码感知力,将其转化为信息尖峰信号.
  • 将生成的尖端信号输入到尖端神经网络 (SNN) 中,用于触摸手势识别.

主要成果:

  • 机械感应器阵列成功地为各种触摸手势生成了不同的尖峰信号.
  • 使用SNN,触摸手势被分类,准确率高达92.5%,使用SNN.
  • 阵列的自动供电性质消除了对外部电源的需求.

结论:

  • 拟议的自动供电机械感应器阵列是触摸式传感器计算的有希望的构建块.
  • 集成TENG和双晶体管使得高效和低成本的触摸传感和尖端编码成为可能.
  • 该系统的高精度和低功耗使其适合物联网应用.