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

224
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...
224

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

The association of obstructive sleep apnea with the frailty index in individuals stratified by cardiovascular-kidney-metabolic syndrome stages.

Medicine·2026
Same author

MT-MRI for detection of renal interstitial fibrosis in renovascular disease.

Scientific reports·2026
Same author

A high-dexterity soft neuroprosthetic hand for daily activities.

Nature communications·2026
Same author

Mitochondrial-derived peptide MOTS-c activates metabolic signaling but blunts reparative function in human mesenchymal stromal cells.

Inflammation and regeneration·2026
Same author

Comparative performance of stress hyperglycemia ratio, glycemic gap, and hemoglobin glycation index for predicting functional outcomes after intravenous thrombolysis in acute ischemic stroke.

Clinical neurology and neurosurgery·2026
Same author

Robust Decomposition of Surface EMG Signals via Lightweight Deep Learning-Based Adaptation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026

相关实验视频

Updated: Jun 20, 2025

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

1.2K

一个基于模型的大脑开关通过周期性运动图像调制为异步大脑-计算机接口.

Jianjun Meng1,2, Songwei Li1,2, Guangye Li1,2

  • 1Department of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China.

Journal of neural engineering
|July 19, 2024
PubMed
概括

这项研究引入了一种新的虚拟物理模型脑开关,可以显著降低脑计算机接口 (BCI) 中的错误阳性率 (FPR). 这种新的方法提高了异步BCI的可用性和实用性.

关键词:
异步的大脑与计算机接口大脑开关大脑开关基于模型的基于模型的模型运动影像图像学

更多相关视频

Non-Invasive Electrical Brain Stimulation Montages for Modulation of Human Motor Function
07:47

Non-Invasive Electrical Brain Stimulation Montages for Modulation of Human Motor Function

Published on: February 4, 2016

13.0K
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

937

相关实验视频

Last Updated: Jun 20, 2025

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

1.2K
Non-Invasive Electrical Brain Stimulation Montages for Modulation of Human Motor Function
07:47

Non-Invasive Electrical Brain Stimulation Montages for Modulation of Human Motor Function

Published on: February 4, 2016

13.0K
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

937

科学领域:

  • 神经科学是一个神经科学.
  • 生物医学工程 生物医学工程
  • 计算机科学 计算机科学

背景情况:

  • 异步大脑计算机接口 (BCI) 在没有预编程结构的情况下解码用户的意图.
  • 目前基于脑电图 (EEG) 的脑开关存在高假阳性率 (FPR),这限制了它们的实际应用.
  • 提高大脑开关的操作模式和可用性对于推进BCI技术至关重要.

研究的目的:

  • 开发一种具有改进的操作模式和可用性的新型大脑开关.
  • 为了降低大脑开关的错误阳性率 (FPR),以提高实用性.
  • 为异步BCI应用优化大脑开关性能.

主要方法:

  • 提出了一种基于虚拟物理模型的新型大脑开关,利用周期性活跃调制.
  • 制定了一个优化问题,以尽量减少触发时间,同时保持所需的FPR.
  • 根据开发的模型获得了数值和分析的近似解决方案.
  • 应用常见空间模式 (CSP) 和优化方法,以进一步增强大脑交换机.

主要成果:

  • 基于运动图像 (MI) 的大脑开关实现了0.8 FPS/h的 FPR,平均触发时间为58秒.
  • 在线设备控制评估表明,与传统的大脑开关相比,FPR的平均值要低得多.
  • 基于MI-CSP的脑开关实现了0.3 FPS/h的平均FPR,并改善了21.6秒的平均触发时间.

结论:

  • 开发的脑开关显著降低了FPRs (少于1 FPs/h),与其他内源方法相比,实现了十倍以上的降低.
  • 反应时间与最先进的方法相比,对非侵入性异步BCI来说是一个显著的进步.
  • 这种方法对BCI技术的广泛临床应用具有前景.