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相关概念视频

Electrocardiogram01:29

Electrocardiogram

2.1K
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...
2.1K
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

424
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....
424
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

482
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...
482
Pulse rhythm01:30

Pulse rhythm

754
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...
754
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

3.3K
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...
3.3K
Electrophysiology of Normal Cardiac Rhythm01:19

Electrophysiology of Normal Cardiac Rhythm

2.0K
The normal cardiac rhythm is a synchronized electrical activity that facilitates the regular and coordinated contraction of the heart muscle. This process is essential for efficient blood circulation throughout the body. The fundamental elements involved in establishing and maintaining this rhythm include the unique electrical properties of cardiac muscle cells, the sinoatrial (SA) node's pacemaker function, the specialized conducting system, and the ionic mechanisms underlying each phase...
2.0K

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相关实验视频

Updated: May 29, 2025

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
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Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

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使用渐进移动平均转换的心电图心跳分类.

Rabah Mokhtari1, Samir Brahim Belhouari2, Khelil Kassoul3

  • 1Computer Science Department, Faculty of Mathematics and Computer Science, University of M'sila, PO Box 166, Ichbilia, 28000, M'sila, Algeria.

Scientific reports
|February 5, 2025
PubMed
概括
此摘要是机器生成的。

一个新的渐进式移动平均转换 (PMAT) 将时间域信号转换为2D表示,以改进心跳分类. 这种方法与二维卷积神经网络 (CNN) 相结合,可以在心电图数据上实现高精度.

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Semi-automated Optical Heartbeat Analysis of Small Hearts
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Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
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相关实验视频

Last Updated: May 29, 2025

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
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Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

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Semi-automated Optical Heartbeat Analysis of Small Hearts
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Semi-automated Optical Heartbeat Analysis of Small Hearts

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

  • 生物医学工程 生物医学工程
  • 信号处理 信号处理
  • 机器学习 机器学习

背景情况:

  • 准确的心电图 (ECG) 心跳分类对于诊断心脏疾病至关重要.
  • 传统的信号处理方法可能难以应对心电图信号的复杂性和可变性.
  • 越来越需要强大的和高效的自动化电图分析技术.

研究的目的:

  • 引入渐进移动平均转换 (PMAT) 作为一种用于将时间域信号转换为2D表示的新方法.
  • 将PMAT与二维卷积神经网络 (CNN) 集成,以增强心电图心跳分类.
  • 评估PMAT-CNN方法在各种ECG数据库中的性能和稳定性.

主要方法:

  • 开发了渐进式移动平均转换 (PMAT) 以使用不同窗口大小的移动平均来创建2D信号表示.
  • 采用2D卷积神经网络 (CNN) 模型,从PMAT生成的2D数据中提取特征并对心电图心跳进行分类.
  • 使用MIT-BIH和INCART心电图数据库验证了该方法,将6种心跳类型分为3个主要类别.

主要成果:

  • 在MIT-BIH数据库中实现了高分类准确度和F1分数:99.09%准确度和92.13%F1分数.
  • 在INCART数据库中获得了98.37%的准确性和79.37%的F1分数.
  • 当在一个数据库上训练的模型在另一个数据库上测试时,证明了高于95%的准确性,包括ST-T欧洲数据库.

结论:

  • 渐进移动平均转换 (PMAT) 与2D-CNN相结合,是一种高效的心电图心跳分类方法.
  • 拟议的方法在不同数据集中表现出卓越的准确性和稳定性,表明其可靠性.
  • 在医疗诊断和医疗保健系统中,PMAT显示出用于自动心脏监测的实际应用的巨大潜力.