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

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

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

21
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...
21
Disturbances in Heart Rhythm01:28

Disturbances in Heart Rhythm

970
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...
970
Mechanism of Cardiac Arrhythmias01:28

Mechanism of Cardiac Arrhythmias

925
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.
925
ECG Interpretation of Arrhythmias I: Sinus Arrhythmias01:16

ECG Interpretation of Arrhythmias I: Sinus Arrhythmias

217
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,...
217
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

5.6K
The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...
5.6K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

602
Introduction
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...
602

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

Severe Cutaneous Adverse Reactions Associated With Newer-Generation Antiseizure Medications: A Real-World Pharmacovigilance Study Based on FAERS and JADER.

CNS neuroscience & therapeutics·2026
Same author

A two-level hierarchy underlies auditory novelty processing in the human brain.

NeuroImage·2026
Same author

Rehabilitation paired with vagus nerve stimulation for motor function of chronic ischemic stroke patients in China: Study protocol of a multicenter randomized controlled trial (Repair Study).

Neuroprotection (Chichester, England)·2026
Same author

An EEG-sEMG Asynchronous Time-Frequency Progressive Fusion Model for Hand Trajectory Estimation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2025
Same author

Resective Surgery for Drug-Resistant Epilepsy in Patients With Tuberous Sclerosis Complex: A Prospective Nationwide Multicenter Cohort Study.

Neurology·2025
Same author

Unified <i>k</i>-space theory of optical coherence tomography.

Advances in optics and photonics·2025
Same journal

RETRACTION: Meta-Analysis of the Prognostic Value of Narcotrend Monitoring of Different Depths of Anesthesia and Different Bispectral Index (BIS) Values for Cognitive Dysfunction after Tumor Surgery in Elderly Patients.

Journal of healthcare engineering·2026
Same journal

Correction to "Representation of Differential Learning Method for Mitosis Detection".

Journal of healthcare engineering·2026
Same journal

RETRACTION: Effect of Combined Etomidate-Ketamine Anesthesia on Perioperative Electrocardiogram and Postoperative Cognitive Dysfunction of Elderly Patients with Rheumatic Heart Valve Disease Undergoing Heart Valve Replacement.

Journal of healthcare engineering·2026
Same journal

RETRACTION: Ensemble Learning-Based Hybrid Segmentation of Mammographic Images for Breast Cancer Risk Prediction Using Fuzzy C-Means and CNN Model.

Journal of healthcare engineering·2026
Same journal

RETRACTION: Wavelet Transform Image Enhancement Algorithm-Based Evaluation of Lung Recruitment Effect and Nursing of Acute Respiratory Distress Syndrome by Ultrasound Image.

Journal of healthcare engineering·2025
Same journal

RETRACTION: lncRNA FGD5-AS1 Regulates Bone Marrow Stem Cell Proliferation and Apoptosis by Affecting miR-296-5p/STAT3 Axis in Steroid-Induced Osteonecrosis of the Femoral Head.

Journal of healthcare engineering·2025
查看所有相关文章

相关实验视频

Updated: Jul 8, 2025

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

3.7K

基于心电图的多类心律失常的分类使用节拍级融合网络.

Junyuan Jing1, Jing Zhang1, Aiping Liu1

  • 1School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China.

Journal of healthcare engineering
|December 11, 2023
PubMed
概括
此摘要是机器生成的。

一个新的节拍水平融合网络 (BLF-Net) 通过对个体心跳进行加权来改善心律失常的分类. 这种深度学习方法可以通过心电图 (ECG) 数据来加强心血管疾病的诊断.

更多相关视频

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
08:22

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

Published on: April 26, 2024

1.8K
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

625

相关实验视频

Last Updated: Jul 8, 2025

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

3.7K
Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
08:22

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

Published on: April 26, 2024

1.8K
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

625

科学领域:

  • 心脏病学 心脏病学
  • 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:

  • 心血管疾病 (CVD) 构成了全球严重的健康威胁.
  • 电心电图 (ECG) 是心血管疾病的关键诊断工具,特别是用于检测心律失常.
  • 深度学习方法,特别是那些结合注意力机制的方法,在心电图分析中表现有前途,但往往侧重于时间点加权.

研究的目的:

  • 引入一种新的深度学习模型,即Beat-Level Fusion Net (BLF-Net),用于多类心律失常的分类.
  • 通过将注意力机制应用于心跳水平而不是仅仅是时间点来解决现有方法的局限性.
  • 从心电图信号提高自动心律失常检测的准确性和可解释性.

主要方法:

  • 拟议的BLF-Net将长时间的ECG信号分割成个别的心跳.
  • 一个神经网络从每个心跳中提取特征.
  • 一个注意力机制根据它们的诊断贡献将权重分配给心跳特征.

主要成果:

  • 与最先进的方法相比,BLF-Net在使用PTB-XL数据库的六个分类任务中表现出更高的性能.
  • 对注意力机制权重的可视化提供了对模型决策过程的见解.
  • 该模型在多类心律失常的分类中取得了很高的准确性.

结论:

  • BLF-Net提供了一种有效和自动化的方法来对心律失常进行分类.
  • 关注心跳水平可以提高心电图分析的诊断能力.
  • 这种方法有可能显著帮助心脏病专家诊断心律不整.