Jove
Visualize
联系我们

相关概念视频

ECG Interpretation of Arrhythmias I: Sinus Arrhythmias01:16

ECG Interpretation of Arrhythmias I: Sinus Arrhythmias

226
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,...
226
Dysrhythmias V: Evaluating Dysrhythmias01:30

Dysrhythmias V: Evaluating Dysrhythmias

40
Dysrhythmias, also known as arrhythmias, are disturbances in the heart's rhythm that range from benign to life-threatening. A thorough evaluation is crucial for appropriate management and involves a comprehensive medical history, physical examination, and various diagnostic tests.Medical HistorySymptoms: Collect detailed information on palpitations, dizziness, syncope, chest pain, and fatigue. Note their onset, frequency, and triggers.Previous Cardiac Issues: Document any history of heart...
40
ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias01:25

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

22
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...
22
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

612
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...
612
Disturbances in Heart Rhythm01:28

Disturbances in Heart Rhythm

977
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...
977
Electrocardiogram01:29

Electrocardiogram

2.4K
An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
2.4K

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

Development, Reliability, and Validity Assessment of a Portable 3D Camera-Based System for Quantifying Postural Sway and Balance.

Sensors (Basel, Switzerland)·2026
Same author

Retinal hyper-reflective foci link retinal and cortical pathology in paediatric multiple sclerosis.

Brain : a journal of neurology·2026
Same author

Multimodal machine learning for distinguishing pediatric multiple sclerosis from non-inflammatory conditions using optical coherence tomography.

Frontiers in neurology·2026
Same author

Machine learning model identifies tibial anatomical variables as potential risk factors for anterior cruciate ligament injury.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA·2026
Same author

Federated Learning in Neurology: Bridging Data Privacy and Artificial Intelligence for Brain Health.

Seminars in neurology·2025
Same author

Streamlined and efficient patient-specific modeling for lumbar spine segmentation and finite element analysis.

Scientific reports·2025
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

相关实验视频

Updated: Jul 11, 2025

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
05:03

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function

Published on: December 11, 2019

8.7K

在分发和分发之外的自我监督的ECG表示学习,用于检测心律失常.

Sahar Soltanieh, Javad Hashemi, Ali Etemad

    IEEE journal of biomedical and health informatics
    |November 10, 2023
    PubMed
    概括

    自主监督学习 (SSL) 在心电图 (ECG) 节律失常检测方面表现出色,在数据集中显示出强烈的概括性. 像SwaV这样的SSL方法通过监督的方法实现了强大的ECG分析,从而实现了竞争性性能.

    科学领域:

    • 心脏病学 心脏病学
    • 机器学习 机器学习
    • 信号处理 信号处理

    背景情况:

    • 电心电图 (ECG) 分析对于诊断心律失常至关重要.
    • 传统的监督学习方法需要大量的标记数据集,这些数据集往往很稀缺或很昂贵,用于获得心电图数据.
    • 自主监督学习 (SSL) 为从未标记的ECG数据中学习表示提供了一个有希望的替代方案.

    研究的目的:

    • 系统地调查SSL方法在ECG心律失常检测方面的有效性.
    • 分析受欢迎的心电图心律失常数据集中的数据分布 (PTB-XL,Chapman,Ribeiro).
    • 评估和比较不同的SSL技术 (SimCRL,BYOL,SwaV) 用于ECG表示学习.

    主要方法:

    • 对 PTB-XL,Chapman 和 Ribeiro ECG 数据集数据分布的新型定量分析.
    • 评估SimCRL,BYOL和SwaV的综合实验,使用各种增强和参数.
    • 交叉数据集培训和测试,以评估分布内 (ID) 和分布外 (OOD) 数据的性能.
    • 详细的每种疾病的绩效分析.

    主要成果:

    • 在评估的SSL方法中,SwaV在ECG表示学习中表现出最好的表现.

    更多相关视频

    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
    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

    637

    相关实验视频

    Last Updated: Jul 11, 2025

    Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
    05:03

    Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function

    Published on: December 11, 2019

    8.7K
    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
    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

    637
  • 与监督的最先进方法相比,SSL方法取得了极具竞争力的结果.
  • SSL技术显示出强大的泛化能力,在ID和OOD心电图数据上几乎具有相同的性能.
  • 每种疾病的分析提供了对SSL方法在不同类型心律失常的性能的见解.

    • 结论:

    • SSL方法在ECG心律失常检测方面非常有效,为监督方法提供了可行的替代方案.
    • SSL技术学习了强大的ECG表示,可以在不同的数据集和条件中很好地概括.
    • 这些发现对开发更容易获得和广泛应用的基于心电图的心律失常检测系统具有重大意义.