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

Seizures: Classification01:13

Seizures: Classification

439
Epilepsy is primarily characterized by unpredictable seizures, either provoked by an identifiable factor, such as injury or illness, or unprovoked, occurring spontaneously without apparent cause.
Seizures are typically classified into two main categories: focal and generalized seizures.
Focal Seizures
Focal seizures originate from specific regions of the brain. These seizures are further sub-classified into two types:
439
Epilepsy and Seizures: Overview01:24

Epilepsy and Seizures: Overview

228
Epilepsy is a chronic neurological disease marked by recurrent, unpredictable seizures. These seizures are caused by abnormal electrical discharges in the brain, leading to behavior, sensation, or consciousness alterations. They can also cause transient impairment of awareness, interfering with daily activities.
Various factors can trigger epilepsy, including genetic factors, brain damage, metabolic causes, and unknown etiology. Diagnosis of epilepsy involves electroencephalography (EEG), which...
228

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 authorSame journal

Pyramid Vision Transformer-Enhanced Conformer Network for Epileptic Seizure Recognition Using MultiChannel EEG Signals.

International journal of neural systems·2026
Same author

Gender Divergence in COPD Phenotypes and Narrowing Urban-Rural Diagnostic Gaps: A Surveillance Study in Chongqing, China, 2020-2024.

International journal of chronic obstructive pulmonary disease·2026
Same author

Advances and challenges from pathological mechanisms to intelligent quantified diagnosis in diabetic optic neuropathy.

Digital health·2026
Same author

Polydopamine-coated TiO<sub>2</sub> nanoparticles endow pectin films with desirable physical and antibacterial properties for preserving perishable fruits.

International journal of biological macromolecules·2026
Same author

Enhanced Informer Network for Stress Recognition and Classification via Spatial and Channel Attention Mechanisms.

International journal of neural systems·2025
Same author

Novel missense variants in COX15 cause oocyte degeneration and female infertility.

Journal of assisted reproduction and genetics·2025
Same journal

Latent Space Projections and Atlases, a Cautionary Tale in Deep Neuroimaging using Autoencoders.

International journal of neural systems·2026
Same journal

Transformer-Based Anomaly Detection for Neurodegenerative Screening in MRI Images.

International journal of neural systems·2026
Same journal

Discrete Wavelet Convolution for Learnable Time-Frequency Representation with Application to Seizure Prediction.

International journal of neural systems·2026
Same journal

Automatic Seizure Detection using Hierarchical Spectral-Temporal Feature Learning with an Imbalance-Aware Transformer.

International journal of neural systems·2026
Same journal

A Time-Frequency Decoupled Contrastive Learning Framework for Electroencephalography-Based Parkinson's Disease Diagnosis.

International journal of neural systems·2026
查看所有相关文章

相关实验视频

Updated: Jul 25, 2025

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
09:32

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients

Published on: December 18, 2016

12.4K

通过图形变压器网络进行性EEG分类.

Jian Lian1, Fangzhou Xu2

  • 1School of Intelligence Engineering, Shandong Management University, Jinan 250357, P. R. China.

International journal of neural systems
|June 29, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的混合深度学习模型,用于使用电脑电图 (EEG) 信号改进发作识别. 新的框架提高了自动诊断的分类准确性和概括性.

关键词:
电脑脑电图 (EEG) 是一种电脑电图.深度学习是一种深度学习.变压器的变压器是一个变压器.

更多相关视频

Use of a Wireless Video-EEG System to Monitor Epileptiform Discharges Following Lateral Fluid-Percussion Induced Traumatic Brain Injury
09:16

Use of a Wireless Video-EEG System to Monitor Epileptiform Discharges Following Lateral Fluid-Percussion Induced Traumatic Brain Injury

Published on: June 21, 2019

25.7K
Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI
11:00

Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI

Published on: March 19, 2021

4.5K

相关实验视频

Last Updated: Jul 25, 2025

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
09:32

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients

Published on: December 18, 2016

12.4K
Use of a Wireless Video-EEG System to Monitor Epileptiform Discharges Following Lateral Fluid-Percussion Induced Traumatic Brain Injury
09:16

Use of a Wireless Video-EEG System to Monitor Epileptiform Discharges Following Lateral Fluid-Percussion Induced Traumatic Brain Injury

Published on: June 21, 2019

25.7K
Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI
11:00

Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI

Published on: March 19, 2021

4.5K

科学领域:

  • 神经学 神经学
  • 人工智能的人工智能
  • 生物医学工程 生物医学工程

背景情况:

  • 深度学习显示了使用电脑电图 (EEG) 信号对发作识别的前景.
  • 从多通道EEG分类活动仍然存在挑战,特别是在保持模型概括方面.
  • 现有的深度学习模型通常使用单个架构,限制它们捕获复杂信号关联的能力.

研究的目的:

  • 解决目前深度学习模型在自动性发作分类中的局限性.
  • 提出一种新的混合深度学习框架,集成图形神经网络和变压器架构.
  • 提高基于EEG的发作检测的准确性和概括性.

主要方法:

  • 开发了一种混合深度学习模型,将图形神经网络 (GNN) 和变压器架构结合起来.
  • 利用GNN来发现多通道EEG信号中的内在关系.
  • 使用变压器来分析不同EEG通道的异质关联.

主要成果:

  • 与最先进的算法相比,拟议的混合深度学习模型在基于时代的性EEG分类中表现出卓越的性能.
  • 在公共数据集上的实验结果验证了集成GNN和变压器方法的有效性.
  • 该方法显示了在自动发作检测中增强泛化的潜力.

结论:

  • 混合GNN转换器深度学习框架提供了一个有希望的解决方案,用于从EEG准确和普遍的发作分类.
  • 这种方法有效地解决了分析发作诊断的多通道EEG信号关联的挑战.
  • 拟议的模型代表了自动化EEG分析的临床应用的有价值的进步.