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

Single-Channel EEG-Based Epileptic Seizure Prediction Using Common Spatial Pattern and Transfer Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Can we identify the category of imagined phoneme from EEG?

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2021
Same author

Classification of Phonological Categories in Imagined Speech using Phase Synchronization Measure.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2021
Same author

Decoding Covert Speech From EEG-A Comprehensive Review.

Frontiers in neuroscience·2021
Same author

VR Glasses based Measurement of Responses to Dichoptic Stimuli: A Potential Tool for Quantifying Amblyopia?

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2020

相关实验视频

Updated: Jul 8, 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

3.8K

从EEG使用转移学习来检测情绪.

Sidharth Sidharth, Ashish Abraham Samuel, Ranjana H

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 12, 2023
    PubMed
    概括

    这项研究引入了一种新的方法,通过使用脑电图 (EEG) 来检测情绪,该方法结合了平均相一致性 (MPC) 和大小平方相一致性 (MSC) 特性. 该方法在主体依赖和主体独立的情绪分类任务中都取得了高准确性.

    科学领域:

    • 神经科学是一个神经科学.
    • 机器学习 机器学习
    • 信号处理 信号处理

    背景情况:

    • 基于脑电图 (EEG) 的情绪检测由于数据有限而面临挑战.
    • 转移学习为复杂的机器学习任务中的数据稀缺提供了潜在的解决方案.

    研究的目的:

    • 开发一种有效的基于EEG的情绪检测系统,使用转移学习和新的功能组合.
    • 在主体依赖和主体独立的场景中评估拟议方法的性能.

    主要方法:

    • 利用Resnet50作为转移学习的基本模型.
    • 在图像矩阵中使用平均相连贯度 (MPC) 和大小平方连贯度 (MSC) 开发了一种新的特征表示.
    • 嵌入式微分 (DE) 功能进入图像矩阵的对角线.
    • 在SEED EEG数据集 (3类) 上使用10倍交叉验证以获得主体依赖的准确性和离开一个主体 (LOSO) 以获得主体依赖的准确性.

    主要成果:

    • 在依赖主体的情绪分类中获得了93.1%的准确性.
    • 在主体独立情绪分类中获得了71.6%的准确性.
    • 这两种准确性都明显超过了三类分类的机会水平.

    更多相关视频

    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
    05:48

    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

    Published on: August 9, 2024

    1.5K
    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
    11:25

    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

    Published on: July 26, 2013

    43.4K

    相关实验视频

    Last Updated: Jul 8, 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

    3.8K
    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
    05:48

    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

    Published on: August 9, 2024

    1.5K
    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
    11:25

    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

    Published on: July 26, 2013

    43.4K

    结论:

    • 结合MPC和MSC特征,显示出基于EEG的情绪分类具有显著前景.
    • 转移学习方法有效地解决了EEG情绪检测中的数据限制.
    • 未来的工作可能会探索数据增强,增强分类器和改进的功能工程.