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相关概念视频

Electrocardiogram01:29

Electrocardiogram

1.9K
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...
1.9K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

470
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...
470
Pulse rhythm01:30

Pulse rhythm

740
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...
740
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

383
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....
383
Instrumentation Amplifier01:25

Instrumentation Amplifier

411
An electrocardiography (ECG) machine is an essential piece of medical equipment used to monitor the electrical activity of the heart. It operates by detecting small electrical changes on the skin that result from the depolarization of the heart muscle during each heartbeat. However, these signals are in the microvolt range and can be easily overwhelmed by noise or interference.
To overcome this challenge, an ECG machine utilizes an instrumentation amplifier. This specialized amplifier is...
411
Disturbances in Heart Rhythm01:28

Disturbances in Heart Rhythm

772
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...
772

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相关实验视频

Updated: May 20, 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

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色:对ECG上的异常检测的预测

Paula Ruiz-Barroso1, Francisco M Castro1, José Miranda2

  • 1Department of Computer Architecture, University of Málaga, Malaga, 29071, Spain.

Computer methods and programs in biomedicine
|April 29, 2025
PubMed
概括
此摘要是机器生成的。

一个新的深度学习系统,FADE,预测正常的心电图信号用于异常检测. 这种方法减少了对标记数据和手动解释的需求,改善了早期心脏异常检测.

关键词:
节律失常 (arrhythmia) 是一种心律失常.深度学习是一种深度学习.域名适应领域适应这是一个ECGECGECGECGECG.预测 预测 预测 预测心脏的跳动是因为心跳.自己监督的自我监督.

更多相关视频

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

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A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
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A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

Published on: December 28, 2012

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相关实验视频

Last Updated: May 20, 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

3.5K
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

8.5K
A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
18:11

A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

Published on: December 28, 2012

24.2K

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:

  • 心血管疾病是导致死亡的主要原因,需要早期检测.
  • 目前的心电图异常检测依赖于耗时的手动解释.
  • 机器学习的进步为ECG分析提供了新的途径.

研究的目的:

  • 提出FADE,一个用于正常ECG预测和异常检测的深度学习系统.
  • 减少对广泛标记数据集和手动心电图解释的依赖.
  • 为了提高检测心脏异常的准确性和效率.

主要方法:

  • 开发了FADE,这是一个以自我监督的方式训练的深度学习系统.
  • 采用一种新的形态学启发的损失函数用于ECG预测.
  • 使用独特的距离功能来比较预测和实际的心电图数据以识别异常.
  • 包含域名适应技术,以实现上下文灵活性.

主要成果:

  • 在异常检测中达到83.84%的平均准确性.
  • 在对正常心电图信号进行分类时,获得了85.46%的准确性.
  • 与以前的方法相比,在检测更广泛的心脏异常方面表现出卓越的性能.

结论:

  • 在早期心脏异常检测方面,FADE提供了卓越的性能.
  • 该系统有效地识别出异常的心跳和心律失常.
  • 在降低成本,远程监控和大规模ECG数据处理方面,FADE具有优势.