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组合生物层次灵活应变传感器用于用机器学习识别手语.

Xuanjie Zong1,2, Nianqiang Zhang1,2, Jilai Wang1

  • 1Key Laboratory of High Efficiency and Clean Mechanical Manufacture of Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan, Shandong 250061, China.

ACS applied materials & interfaces
|July 16, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的灵活应变传感器 (CBH传感器),其灵感来源于自然. 它实现了广泛的传感范围和高灵敏度,使准确的手势语言手势识别能够改善人机交互.

关键词:
仿生生物技术 (BIONIC) 是一种灵活的应变传感器层次结构是指层次结构的结构.机器学习是机器学习.标志性语言识别 标志性语言识别

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科学领域:

  • 材料科学 材料科学 材料科学
  • 生物医学工程 生物医学工程
  • 可穿戴技术可穿戴技术

背景情况:

  • 灵活的应变传感器对于可穿戴设备和健康监测至关重要.
  • 同时实现广泛的传感范围和高灵敏度仍然是一个重大挑战.
  • 现有的传感器往往会对特定应用的性能产生影响.

研究的目的:

  • 开发一种灵活的应变传感器,具有平衡的广泛传感范围和高灵敏度.
  • 创建一个传感器,利用一个交叉尺度组合的生物层次结构设计.
  • 为了展示传感器在手势语言手势识别中的应用.

主要方法:

  • 采用了结合性的生物层次设计,整合了微观和宏观特征.
  • 三维打印,预拉伸和模具转移技术被用于制造传感器.
  • 传感器的性能被评估为其传感范围,灵敏度,以及在手势识别中的应用.

主要成果:

  • 组合生物基层灵活应变传感器 (CBH传感器) 实现了150%的广泛传感范围.
  • 传感器表现出高灵敏度,其测量因子高达2416.67.7.
  • 一系列CBH传感器成功地使用机器学习识别了九个手势语言手势,准确度为100%.

结论:

  • 该CBH传感器有效地解决了平衡传感范围和灵敏度的挑战.
  • 该传感器显示了为聋人和听力障碍者社区提供沟通的巨大潜力.
  • 人与计算机接口和以手势驱动的交互中的应用是有希望的.