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相关概念视频

Design Example: Resistive Touchscreen01:14

Design Example: Resistive Touchscreen

288
A device engineer plays a crucial role in designing user interfaces for mobile devices. One such interface is the resistive touchscreen, which fundamentally consists of two metallic layers: a flexible upper layer and a rigid lower layer, separated by a narrow gap. The high resistance between these two layers is a key characteristic of this design.
When a user touches the screen, the two layers make contact at a specific point known as the touchpoint. This contact reduces the resistance between...
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Perception of Sound Waves01:01

Perception of Sound Waves

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The human ear is not equally sensitive to all frequencies in the audible range. It may perceive sound waves with the same pressure but different frequencies as having different loudness. Moreover, the perception of sound waves depends on the health of an individual's ears, which decays with age. The health of one's ears may also be affected by regular exposure to loud noises.
The pitch of a sound depends on the frequency and the pressure amplitude of the source. Two sounds of the same...
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相关实验视频

Updated: Jun 9, 2025

Applying Incongruent Visual-Tactile Stimuli during Object Transfer with Vibro-Tactile Feedback
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Applying Incongruent Visual-Tactile Stimuli during Object Transfer with Vibro-Tactile Feedback

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在分布式触觉设备中解码粗感知.

Sitangshu Chatterjee1, Sylvia Tan2, Changhyun Choi1

  • 1Department of Mechanical Engineering, Texas A&M University, 3123 TAMU, College Station, TX 77843, USA.

PNAS nexus
|October 30, 2024
PubMed
概括
此摘要是机器生成的。

一个新的模型通过分析皮肤应变变化和侧面剪切力,通过触觉设备准确预测感知粗度. 这有助于实现现实的纹理染和触觉设备设计.

关键词:
触觉学是一种触觉学.感知 感知 感知 感知粗性 粗性 粗性的皮肤 机械 皮肤 机械

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科学领域:

  • 触觉技术是一种触觉技术.
  • 人与计算机的互动.
  • 感官神经科学是一种神经科学.

背景情况:

  • 通过触觉设备实现现实的纹理感知仍然是一个重大挑战.
  • 现有的粗感知预测模型是有限的,无法考虑刺激的侧向执行和空间分散.
  • 皮肤中的机械受体处理触觉信息,使其能够感知像粗等表面特性.

研究的目的:

  • 为感知粗度开发一个预测模型,以解释任意的外部刺激.
  • 来自各种触觉设备的现有心理物理实验数据对模型进行验证.
  • 为了阐明关键的物理机制,基础的粗感知在响应触觉反.

主要方法:

  • 开发一种新的计算模型来预测感知粗度.
  • 模型的验证使用已发表的心理物理实验结果.
  • 分析皮肤应变变化和侧切削力作为关键预测因素.

主要成果:

  • 开发的模型准确地预测了不同触觉设备和刺激的感知粗度.
  • 接触区域的应变变化的变化与粗感知有很强的相关性.
  • 包括横切削力对于准确的粗度预测至关重要.

结论:

  • 新模型在预测触觉纹理感知,特别是粗度方面取得了重大进展.
  • 了解应变变化和侧 shear 力的作用,可以更深入地了解触觉传感机制.
  • 这种模型可以加速触觉设备的设计和优化,减少对经验测试的依赖.