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

Dysrhythmias II: Classification of Tachyarrhythmias01:28

Dysrhythmias II: Classification of Tachyarrhythmias

141
Tachyarrhythmias are a type of dysrhythmia where the heart rate exceeds 100 beats per minute. Here are some common types of tachyarrhythmias:Sinus TachycardiaSinus tachycardia originates from increased impulses from the sinus node, leading to an elevated heart rate. It is often triggered by stress, fever, or exercise.Patients may experience palpitations, a sensation of a racing heart, dizziness, and chest discomfort.Causes and Risk Factors: Common causes include physical exertion, emotional...
141
Disturbances in Heart Rhythm01:29

Disturbances in Heart Rhythm

1.3K
Arrhythmia or dysrhythmia refers to an abnormal heart rhythm caused by a defect in the heart's conduction system. It can cause the heart to beat irregularly, too quickly, or too slowly, leading to symptoms like chest pain, shortness of breath, and fainting. Factors such as stress, caffeine, alcohol, nicotine, cocaine, certain drugs, congenital defects, diseases, and electrolyte abnormalities can trigger arrhythmias.
Arrhythmias are categorized by their speed, rhythm, and origin. A slow heart...
1.3K
Mechanism of Cardiac Arrhythmias01:28

Mechanism of Cardiac Arrhythmias

1.1K
Arrhythmias are irregular heart rhythms occurring when the heart's electrical impulses become abnormal. These disturbances can lead to various symptoms, depending on their severity and the underlying cause. Some common factors contributing to arrhythmias include hypoxia, ischemia, electrolyte imbalances, excessive catecholamine exposure, drug toxicity, and muscle overstretching. Arrhythmias can be classified into two main types based on the rate and site of origin of abnormal heart rhythms.
1.1K
Dysrhythmias I: Introduction01:15

Dysrhythmias I: Introduction

172
Dysrhythmias refers to abnormalities in the heart's rhythm. They result from disruptions in the heart's electrical conduction system, which includes the sinoatrial(SA)node, atrioventricular(AV) node, the bundle of His, bundle branches, and Purkinje fibers.Definition and PathophysiologyDysrhythmias result from disorders of impulse formation, impulse conduction, or both. The heart contains specialized cells in the sinoatrial node, atrioventricular node, and the bundle of His and Purkinje fibers...
172
Pulse rhythm01:30

Pulse rhythm

940
Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...
940
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

152
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
152

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

Nanotechnology enabled proximity-induced protein degradation from multiscale bottlenecks to precision therapeutics.

Advanced drug delivery reviews·2026
Same author

Differential freezing responses in gill side flesh vs. collar flesh of bighead carp (<i>Aristichthys nobilis</i>) head: the role of ice crystal formation in protein and lipid deterioration.

Food chemistry: X·2026
Same author

New-generation advanced Nano-PROTACs as potential therapeutic agents in cancer therapy.

Journal of controlled release : official journal of the Controlled Release Society·2026
Same author

Peptide-drug conjugates in tumor therapy: Current advances and future perspectives.

Cancer letters·2025
Same author

Effect of ice crystal formation on the mechanical and protein properties of grass carp (Ctenopharyngodon idella) flesh: Contributions of salt ions and freezing rate.

Food chemistry·2025
Same author

ECG classification efficient modeling with artificial bee colony optimization data augmentation and attention mechanism.

Mathematical biosciences and engineering : MBE·2024

相关实验视频

Updated: Sep 19, 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

4.2K

基于具有注意力机制的多输入卷积神经网络的心律失常分类.

Bin Zheng1, Wenbo Luo1, Mingming Zhang1,2

  • 1School of Mathematics, Statistics and Mechanics, Beijing University of Technology, Beijing, China.

PloS one
|June 17, 2025
PubMed
概括

这项研究引入了一种新的深度学习模型,用于使用多尺度心电图分析进行心律失常的分类. 先进的算法实现了高精度,改善了心律失常的检测.

科学领域:

  • 生物医学工程 生物医学工程
  • 人工智能在医学中的应用
  • 心脏病学 心脏病学

背景情况:

  • 心律失常会带来严重的健康风险,包括中风和心脏骤停.
  • 深度学习已经改善了心电图分析,但信号变化和数据不平衡等挑战仍然存在.
  • 现有的方法经常在特征表示和单模输入方面扎.

研究的目的:

  • 开发一种使用多输入卷积神经网络 (CNN) 与挤压刺激 (SE) 注意力机制的新型心律失常分类算法.
  • 整合ECG信号的多尺度时间频率表示,以增强特征学习.
  • 为了提高自动心律失常检测的准确性和稳定性.

主要方法:

  • 一个双分支CNN架构处理ECG信号分成两个时间分辨率.
  • 使用短时间里埃转换 (STFT) 集成多尺度时间频率表示.
  • 挤压激发 (SE) 块来增强通道间的依赖性和特征优先级.
  • 一个融合策略,通过双立方互波和元素智能总和结合特征地图.

主要成果:

  • 拟议的模型实现了高分类准确性:在MIT-BIH数据库中达到99.13%,在SPH数据库中达到95.84%.
  • 获得了优秀的宏观F1分数:94.46% (MIT-BIH) 和95.91% (SPH).

相关实验视频

Last Updated: Sep 19, 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

4.2K
  • 该模型的性能优于现有的几种最先进的心律失常分类方法.
  • 结论:

    • 新型多输入CNN与SE注意力在心律失常分类中表现出卓越的表现.
    • 多尺度特征和注意力机制的整合提高了稳定性和准确性.
    • 拟议的算法显示出在心律失常诊断中临床应用的巨大潜力.