Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

STAR-ViT: A Spatially Transformed and Adversarially Realigned Vision Transformer for Pathogen Classification in Pediatric Pneumonia.

IEEE journal of biomedical and health informatics·2026
Same author

Colorimetric Detection and Intracellular Imaging of Polynucleotide Kinase by the Phosphorylation-Induced Assembly of DNA-Modified Gold Nanoparticles.

Analytical chemistry·2026
Same author

Unraveling the complex interplay between glymphatic function, age, and brain structure in school-aged children with autism spectrum disorder.

Brain imaging and behavior·2026
Same author

The Association Between Bending Photoplethysmography Waveform Area Index and Congestive Heart Failure.

Clinical cardiology·2026
Same author

The CARE Program: An Initiative of Patient-Focused Drug Development for Rare Diseases by NMPA.

Therapeutic innovation & regulatory science·2026
Same author

Defect Passivation and Crystallization Regulation in Wide-Bandgap Perovskites via p-Cyanobenzenesulphonamide Molecular Additive.

The journal of physical chemistry letters·2026

相关实验视频

Updated: Jul 12, 2025

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
08:15

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

549

机器学习支持的智能手势识别和通信系统使用打印式应变传感器.

Minglu Hu1, Pei He1, Weikai Zhao1

  • 1Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, P. R. China.

ACS applied materials & interfaces
|October 26, 2023
PubMed
概括

研究人员开发了一款带有印制传感器的智能手套,用于手势识别. 该系统在分类手势方面实现了高精度 (高达99.4%),使人机交互和机器人手控制成为可能.

关键词:
这是手势识别,是手势识别.人机交互的人机交互机器学习是机器学习.印制的应变传感器可以穿戴的电子产品.

更多相关视频

Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs
03:55

Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs

Published on: October 27, 2023

2.2K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

3.8K

相关实验视频

Last Updated: Jul 12, 2025

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
08:15

Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

Published on: March 28, 2025

549
Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs
03:55

Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs

Published on: October 27, 2023

2.2K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

3.8K

科学领域:

  • 材料科学 材料科学 材料科学
  • 机器人技术 机器人技术 机器人技术
  • 人工智能的人工智能

背景情况:

  • 手势识别对于人机交互至关重要,提供丰富的信息传输.
  • 开发直观和准确的手势识别系统仍然是一个活跃的研究领域.

研究的目的:

  • 创建一个智能系统,使用新型智能手套进行准确的手势识别.
  • 为了证明系统在分类手语和抓物体手势方面的能力.
  • 通过基于手势的人机交互来实现基本的沟通和控制.

主要方法:

  • 使用印刷碳纳米管-石墨烯/PDMS应变传感器制造智能手套.
  • 开发一个定制的人工神经网络用于手势分类.
  • 创建用于手语和抓物体手势的数据集.
  • 与机器人手进行集成,以响应运动.

主要成果:

  • 智能手套展示了出色的舒适性和可穿戴性.
  • 该系统的平均分类准确率为97%,在特定的手势群体中达到99.4%.
  • 连接的机器人手成功地模仿了人类手势,实现了简单的手势交流.

结论:

  • 开发的智能手套系统为HMI中先进的手势识别提供了可行和实用的解决方案.
  • 高精度和机器人集成突出了直观的人机协作的潜力.
  • 这项技术为手语翻译,虚拟现实和辅助机器人技术的各种应用铺平了道路.