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

Brain Imaging01:14

Brain Imaging

1.0K
Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
1.0K

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

Electric Field-Driven Dynamic Surface Topography of Pyrene-Linked Graphene Oxide Multilayer Film.

ACS applied materials & interfaces·2026
Same author

Florzolotau (18F) retention is linked to neuropsychological performance in tauopathy.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2026
Same author

Erratum: Robustness analysis of decoding SSVEPs in humans with head movements using a moving visual flicker (2019<i>J. Neural Eng</i>.<b>17</b>016009).

Journal of neural engineering·2026
Same author

Biomarkers.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Alzheimer's Imaging Consortium.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Investigating the Impact of IMU Sensor Quantity on Locomotion Recognition Performance Using Neural Networks for Powered Lower-Limb Prostheses.

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

相关实验视频

Updated: May 6, 2026

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

13.7K

基于运动图像的大脑与计算机接口的频道和标签翻转数据增强.

Takayuki Hoshino, Suguru Kanoga, Atsushi Aoyama

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 5, 2025
    PubMed
    概括

    对脑计算机接口 (BCI) 的数据增强至关重要. 一种新的道和标签翻转方法通过利用大脑信号对称性来提高运动图像分类的准确性.

    科学领域:

    • 神经科学是一个神经科学.
    • 机器学习 机器学习
    • 生物医学工程 生物医学工程

    背景情况:

    • 机器图像大脑计算机接口 (BCI) 的高分类准确性需要广泛的训练数据.
    • 从用户那里获取大型数据集往往是不切实际的,这给BCI开发造成了瓶.
    • 数据增强 (DA) 为扩展有限的训练数据集提供了一个可行的解决方案.

    研究的目的:

    • 为了引入一种新的数据增强技术,道和标签翻转DA,用于电机图像BCI.
    • 为了利用神经科学原理的对称性之间的左手和右手运动图像.
    • 为了提高BCI分类模型的性能,使用有限的数据.

    主要方法:

    • 提出了一种新的道和标签翻转数据增强方法.
    • 利用OpenBMI数据集与54名参与者执行左手和右手运动图像任务的脑电图.
    • 使用三个经典机器学习模型 (过器银行常见空间模式特征) 和一个深度学习模型 (原始信号输入) 评估性能.

    主要成果:

    • 拟议的道和标签翻转DA方法显著提高了平均分类准确性.
    • 相比之下,一个简单的道翻转DA方法没有标签改变导致分类准确度下降.
    • 这些发现表明,在BCI数据增强中,将标签翻转与通道翻转相结合的有效性.

    更多相关视频

    Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
    09:42

    Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

    Published on: September 1, 2023

    1.1K
    Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality
    10:14

    Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality

    Published on: May 10, 2024

    847

    相关实验视频

    Last Updated: May 6, 2026

    An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
    10:51

    An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

    Published on: March 10, 2011

    13.7K
    Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
    09:42

    Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

    Published on: September 1, 2023

    1.1K
    Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality
    10:14

    Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality

    Published on: May 10, 2024

    847

    结论:

    • 频道和标签翻转DA是一种有效的策略,用于提高电机图像BCI性能.
    • 这种方法通过利用固有的神经信号特性来解决有限的训练数据的挑战.
    • 该研究强调了考虑BCI在DA中的标签操纵的重要性.