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

Alternative splicing of PeGA20ox1 impairs PeRAP2-1-mediated GA/ABA homeostasis leading to short internodes in the dwarf variant of Moso bamboo, Phyllostachys edulis 'Heterocycla'.

The New phytologist·2026
Same author

The brain-gut-skin axis in inflammatory and disfiguring skin diseases: mechanistic insights, clinical correlations, and therapeutic strategies.

Frontiers in immunology·2026
Same author

The module of PeGLK1-1-PeWRKY111-PePMHA9 orchestrates stomatal aperture to enhance photosynthetic capacity in bamboo.

Journal of advanced research·2026
Same author

MSRCTNet: a novel multi-scale capsule triplet network for efficient redundant frame removal in wireless capsule endoscopy videos.

Scientific reports·2026
Same author

Retinal Pigment Epithelium-Targeting Gene Therapy Corrects Ocular Symptoms in Mouse and Rat Models of Oculocutaneous Albinism Type I.

MedComm·2025
Same author

Trans-cinnamic acid coordinates PAL repression and C4H induction to modulate lignification in bamboo.

Plant physiology·2025

相关实验视频

Updated: Jun 4, 2025

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

2.6K

基于EEG的情绪识别使用多尺度动态CNN和封闭式变压器.

Zhuoling Cheng1, Xuekui Bu1, Qingnan Wang2

  • 1School of Electronic Information and Electrical Engineering, Yangtze University, Jingzhou, 434100, Hubei, China.

Scientific reports
|December 29, 2024
PubMed
概括
此摘要是机器生成的。

这项研究介绍了MSDCGTNet,这是一种从电脑电图 (EEG) 信号中识别情绪的新方法. 该方法实现了高精度和效率,为脑机接口应用提供了强大的解决方案.

关键词:
电脑电流信号 电脑电流信号门式变压器编码器编码器多个尺度的动态1D CNN时间卷积网络的时间卷积网络.时间空间的特征.

更多相关视频

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

33.6K
Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury
05:51

Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury

Published on: May 15, 2016

9.0K

相关实验视频

Last Updated: Jun 4, 2025

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

2.6K
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

33.6K
Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury
05:51

Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury

Published on: May 15, 2016

9.0K

科学领域:

  • 神经科学是一个神经科学.
  • 人工智能的人工智能
  • 信号处理 信号处理

背景情况:

  • 情绪显著影响人类的认知和决策.
  • 电脑电图 (EEG) 是一种有价值的情感识别工具,因为它具有时间分辨率,可移植性和成本效益.

研究的目的:

  • 提出一种全新的端到端方法,MSDCGTNet,用于从EEG信号中准确有效地识别情绪.
  • 利用多尺度动态卷积神经网络 (CNN) 和门式变压器进行增强的特征提取和依赖性建模.

主要方法:

  • 利用多尺度动态CNN从原始EEG信号中提取空间和光谱特征,最大限度地减少信息丢失和计算成本.
  • 采用了带有多头自我注意力的门式变压器编码器,以高效地捕获全球EEG信号依赖.
  • 应用时间卷积网络用于提取时间特征,然后是用于情绪识别的分类模块.

主要成果:

  • 该MSDCGTNet方法在情感识别任务中表现出高准确性和效率.
  • 在DEAP,SEED和SEED_IV数据集上进行评估,证实了该方法的有效性.
  • 这种方法被证明是稳固的,适合实际应用.

结论:

  • MSDCGTNet提供了一种有价值和有效的解决方案,用于使用EEG信号进行情绪识别.
  • 该方法解决了现有技术的局限性,推进了脑计算机接口 (BCI) 的领域.
  • 拟议的方法增强了实时情绪识别能力.