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

508
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...
508
ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias01:25

ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias

472
Arrhythmia is a condition characterized by an irregular heart rhythm, with ECG changes that differ based on its origin and nature. The types of arrhythmias discussed below include atrial, junctional, and ventricular arrhythmias.Atrial ArrhythmiasPremature Atrial Complexes (PACs): PACs are early atrial beats caused by stress, caffeine, alcohol, electrolyte imbalances, hypoxia, hyperthyroidism, or certain medications (e.g., bronchodilators and decongestants). The ECG shows early P waves with an...
472
Disturbances in Heart Rhythm01:29

Disturbances in Heart Rhythm

2.6K
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...
2.6K
Dysrhythmias III: Characteristics of Dysrhythmias01:29

Dysrhythmias III: Characteristics of Dysrhythmias

425
Dysrhythmias, also known as arrhythmias, are irregular heart rhythms that result from abnormal electrical activity in the heart, affecting its ability to circulate blood efficiently. Tachyarrhythmias, a subset of dysrhythmias, are characterized by abnormally fast heart rates exceeding 100 beats per minute. Here are some types of tachyarrhythmias with their distinct ECG features:Sinus Tachycardia:Sinus tachycardia presents a regular heart rhythm with an increased rate of 101-180 beats per...
425
Mechanism of Cardiac Arrhythmias01:28

Mechanism of Cardiac Arrhythmias

1.7K
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.
1.7K
ECG Interpretation of Arrhythmias I: Sinus Arrhythmias01:16

ECG Interpretation of Arrhythmias I: Sinus Arrhythmias

767
Arrhythmias are disturbances in the heart's rhythm that lead to abnormal heartbeats. These irregularities can originate from different parts of the heart and are classified based on their origin and nature.
Types of Arrhythmias
Sinus Node Arrhythmias
Sinus Bradycardia: Originating from the sinoatrial (SA) node, sinus bradycardia involves slower impulses, resulting in a heart rate of less than 60 beats per minute (bpm). Causes include sleep, vagal stimulation, beta-blockers, hypothyroidism,...
767

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

PKGPT: Expert-Orchestrated Recursive LLM Agent for Automated NONMEM PopPK Modeling with Human Benchmarking.

Pharmaceutics·2026
Same author

Necrotic Cells Alter IRE1α-XBP1 Signaling and Induce Transcriptional Changes in Glioblastoma.

International journal of molecular sciences·2026
Same author

Fabrication of immune-enhancing vesicles from reassembled yeast vacuolar membranes.

Colloids and surfaces. B, Biointerfaces·2025
Same author

Comprehensive Profiling of Serum Exosomes by a Multi-Omics Approach Reveals Potential Diagnostic Markers for Brain Metastasis in Lung Cancer.

Cancers·2025
Same author

Population pharmacokinetics of erlotinib in patients with non-small cell lung cancer (NSCLC): A model-based meta-analysis.

Computers in biology and medicine·2025
Same author

Exosome-based targeted delivery of NF-κB ameliorates age-related neuroinflammation in the aged mouse brain.

Experimental & molecular medicine·2025

相关实验视频

Updated: Jan 18, 2026

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
06:07

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

4.3K

ECG-GraphNet:基于图形卷积网络的高级心律失常分类.

Myeonghun Lee1,2, Jiwoo Lim1,3, JinKook Kim1,4

  • 1HUINNO Co., Ltd., Seoul, Republic of Korea.

Heart rhythm O2
|September 8, 2025
PubMed
概括

一个新的深度学习模型,电心电图卷积网络 (ECG-GraphNet),准确地分类心律失常. 这种新的方法有望改善心律障碍的临床诊断和监测.

关键词:
节律失常 (arrhythmia) 是一种心律失常.心血管疾病是什么心血管疾病深度学习是一种深度学习.电心电图 (ECG) 是一种心电图.图表 卷积网络 卷积网络机器学习 机器学习

更多相关视频

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
10:17

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

1.6K
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

12.9K

相关实验视频

Last Updated: Jan 18, 2026

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
06:07

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

4.3K
Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
10:17

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

1.6K
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

12.9K

科学领域:

  • 人工智能在医学中的应用
  • 心脏病学 心脏病学
  • 信号处理 信号处理

背景情况:

  • 深度学习增强了医疗诊断,特别是心电图 (ECG) 分析.
  • 准确地分类心律不整仍然是临床实践中的一个重大挑战.

研究的目的:

  • 引入心电图卷积网络 (ECG-GraphNet),这是一个用于分类心律失常的新型图形卷积网络.
  • 为了将心律失常分为正常 (N),超心室外 (S) 和心室外 (V) 节拍.

主要方法:

  • ECG-GraphNet使用图形表示,其中ECG波 (P,QRS,T) 是节点.
  • 一种以QRS为中心的加权平均汇集方法增强了节拍特定特征提取.
  • 对节点特征,边界定义,数据增强和架构的系统探索优化了模型设计,使用328名患者的10秒单线心电图记录.

主要成果:

  • 经过5倍交叉验证,优化的ECG-GraphNet通过5倍交叉验证实现了88.61%的宏F1得分.
  • 可扩展性测试证实了稳定性,在各种心电图模式和大小中,Macro F1得分为85.21%和87.03%.

结论:

  • ECG-GraphNet为心律失常的分类提供了一种新且有效的方法.
  • 这些发现强调了ECG-GraphNet在推进临床诊断和患者监测方面的潜力.