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相关概念视频

Electrocardiogram01:29

Electrocardiogram

2.3K
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...
2.3K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

599
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...
599
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

5.3K
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...
5.3K
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

881
An electrocardiogram (ECG)graphically represents the heart's electrical activity on ECG paper or a monitor.
Components of the Electrocardiogram
The primary components of a normal ECG waveform in Normal sinus rhythm(NSR) include the P wave, PR interval, QRS complex, ST segment, T wave, and occasionally a U wave.
ECG waveforms are divided by vertical and horizontal lines at standard intervals.
The horizontal axis measures time and rate, and the vertical axis measures amplitude or voltage....
881
Pulse rhythm01:30

Pulse rhythm

798
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...
798

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相关实验视频

Updated: Jul 2, 2025

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

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联合时空特征受约束 自主监督 心电图表现学习学习

Ao Ran1, Huafeng Liu1

  • 1State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Zheda Road 38#, Hangzhou, 310027 China.

Biomedical engineering letters
|February 20, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了用于心电图 (ECG) 分析的自我监督学习方法,减少对标记数据的依赖. 这种新的方法实现了与使用较少数据的监督方法相当的性能,并提高了心律失常的分类和定位的准确性.

关键词:
节律失常的分类类别是心律失常.电心电图 (ECG) 是一种心电图.自己监督的自我监督.时空特征是时间空间特征.

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Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
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Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
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Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

Published on: January 8, 2013

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相关实验视频

Last Updated: Jul 2, 2025

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

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

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Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
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Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

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科学领域:

  • 生物医学工程 生物医学工程
  • 人工智能的人工智能
  • 心脏病学 心脏病学

背景情况:

  • 电心电图 (ECG) 诊断因依赖标记数据而受到限制.
  • 现有的自主监督的心电图方法缺乏有效性或需要广泛的专家注释.
  • 需要有效的,不那么监督的方法来学习ECG表示.

研究的目的:

  • 开发一种自我监督的学习方法,用于一般的ECG表示.
  • 为了减少对下游诊断任务的标记ECG数据的依赖.
  • 提高ECG分析的效率和准确性.

主要方法:

  • 提出了一种自主监督的空间时空联合检测方法,用于ECG.
  • 动态掩盖的心电图信号 (时间) 和破坏的领先顺序 (空间).
  • 重建了原始信号,并预测了用于模型训练的领先数字.

主要成果:

  • 该方法有效地学习ECG表示,在公共和私人数据集上验证.
  • 使用仅60%的标记数据,实现了与监督方法相似的性能.
  • 与随机初始化相比,对分类和定位任务的准确性有1.3%和8.6%的改进.

结论:

  • 自主监督学习是可行的学习有效的ECG表示.
  • 拟议的方法为ECG分析提供了传统监督学习的有希望的替代方案.
  • 这种方法可以显著减少对专家注释的ECG数据集的需求.